{ "session_id": "20260620_094935_4e338c", "model": "kimi-k2.7-code", "base_url": "https://ollama.com/v1", "platform": "telegram", "session_start": "2026-06-20T09:49:35.790631", "last_updated": "2026-06-20T09:59:35.968485", "system_prompt": "You are Hermes Agent, an intelligent AI assistant created by Nous Research. You are helpful, knowledgeable, and direct. You assist users with a wide range of tasks including answering questions, writing and editing code, analyzing information, creative work, and executing actions via your tools. You communicate clearly, admit uncertainty when appropriate, and prioritize being genuinely useful over being verbose unless otherwise directed below. Be targeted and efficient in your exploration and investigations.\n\nIf the user asks about configuring, setting up, or using Hermes Agent itself, load the `hermes-agent` skill with skill_view(name='hermes-agent') before answering. Docs: https://hermes-agent.nousresearch.com/docs\n\nConversation started: Saturday, June 20, 2026 09:49 AM\nModel: kimi-k2.7-code\nProvider: custom\n\nYou are on a text messaging communication platform, Telegram. Standard markdown is automatically converted to Telegram format. Supported: **bold**, *italic*, ~~strikethrough~~, ||spoiler||, `inline code`, ```code blocks```, [links](url), and ## headers. Telegram has NO table syntax — prefer bullet lists or labeled key: value pairs over pipe tables (any tables you do emit are auto-rewritten into row-group bullets, which you can produce directly for cleaner output). You can send media files natively: to deliver a file to the user, include MEDIA:/absolute/path/to/file in your response. Images (.png, .jpg, .webp) appear as photos, audio (.ogg) sends as voice bubbles, and videos (.mp4) play inline. You can also include image URLs in markdown format ![alt](url) and they will be sent as native photos.", "tools": [ { "type": "function", "function": { "name": "process", "description": "Manage background processes started with terminal(background=true). Actions: 'list' (show all), 'poll' (check status + new output), 'log' (full output with pagination), 'wait' (block until done or timeout), 'kill' (terminate), 'write' (send raw stdin data without newline), 'submit' (send data + Enter, for answering prompts), 'close' (close stdin/send EOF).", "parameters": { "type": "object", "properties": { "action": { "type": "string", "enum": [ "list", "poll", "log", "wait", "kill", "write", "submit", "close" ], "description": "Action to perform on background processes" }, "session_id": { "type": "string", "description": "Process session ID (from terminal background output). Required for all actions except 'list'." }, "data": { "type": "string", "description": "Text to send to process stdin (for 'write' and 'submit' actions)" }, "timeout": { "type": "integer", "description": "Max seconds to block for 'wait' action. Returns partial output on timeout.", "minimum": 1 }, "offset": { "type": "integer", "description": "Line offset for 'log' action (default: last 200 lines)" }, "limit": { "type": "integer", "description": "Max lines to return for 'log' action", "minimum": 1 } }, "required": [ "action" ] } } }, { "type": "function", "function": { "name": "terminal", "description": "Execute shell commands on a Linux environment. Filesystem usually persists between calls.\n\nDo NOT use cat/head/tail to read files — use read_file instead.\nDo NOT use grep/rg/find to search — use search_files instead.\nDo NOT use ls to list directories — use search_files(target='files') instead.\nDo NOT use sed/awk to edit files — use patch instead.\nDo NOT use echo/cat heredoc to create files — use write_file instead.\nReserve terminal for: builds, installs, git, processes, scripts, network, package managers, and anything that needs a shell.\n\nForeground (default): Commands return INSTANTLY when done, even if the timeout is high. Set timeout=300 for long builds/scripts — you'll still get the result in seconds if it's fast. Prefer foreground for short commands.\nBackground: Set background=true to get a session_id. Two patterns:\n (1) Long-lived processes that never exit (servers, watchers).\n (2) Long-running tasks with notify_on_complete=true — you can keep working on other things and the system auto-notifies you when the task finishes. Great for test suites, builds, deployments, or anything that takes more than a minute.\nFor servers/watchers, do NOT use shell-level background wrappers (nohup/disown/setsid/trailing '&') in foreground mode. Use background=true so Hermes can track lifecycle and output.\nAfter starting a server, verify readiness with a health check or log signal, then run tests in a separate terminal() call. Avoid blind sleep loops.\nUse process(action=\"poll\") for progress checks, process(action=\"wait\") to block until done.\nWorking directory: Use 'workdir' for per-command cwd.\nPTY mode: Set pty=true for interactive CLI tools (Codex, Claude Code, Python REPL).\n\nDo NOT use vim/nano/interactive tools without pty=true — they hang without a pseudo-terminal. Pipe git output to cat if it might page.\n", "parameters": { "type": "object", "properties": { "command": { "type": "string", "description": "The command to execute on the VM" }, "background": { "type": "boolean", "description": "Run the command in the background. Two patterns: (1) Long-lived processes that never exit (servers, watchers). (2) Long-running tasks paired with notify_on_complete=true — you can keep working and get notified when the task finishes. For short commands, prefer foreground with a generous timeout instead.", "default": false }, "timeout": { "type": "integer", "description": "Max seconds to wait (default: 180, foreground max: 600). Returns INSTANTLY when command finishes — set high for long tasks, you won't wait unnecessarily. Foreground timeout above 600s is rejected; use background=true for longer commands.", "minimum": 1 }, "workdir": { "type": "string", "description": "Working directory for this command (absolute path). Defaults to the session working directory." }, "pty": { "type": "boolean", "description": "Run in pseudo-terminal (PTY) mode for interactive CLI tools like Codex, Claude Code, or Python REPL. Only works with local and SSH backends. Default: false.", "default": false }, "notify_on_complete": { "type": "boolean", "description": "When true (and background=true), you'll be automatically notified exactly once when the process finishes. **This is the right choice for almost every long-running task** — tests, builds, deployments, multi-item batch jobs, anything that takes over a minute and has a defined end. Use this and keep working on other things; the system notifies you on exit. MUTUALLY EXCLUSIVE with watch_patterns — when both are set, watch_patterns is dropped.", "default": false }, "watch_patterns": { "type": "array", "items": { "type": "string" }, "description": "Strings to watch for in background process output. HARD RATE LIMIT: at most 1 notification per 15 seconds per process — matches arriving inside the cooldown are dropped. After 3 consecutive 15-second windows with dropped matches, watch_patterns is automatically disabled for that process and promoted to notify_on_complete behavior (one notification on exit, no more mid-process spam). USE ONLY for truly rare, one-shot mid-process signals on LONG-LIVED processes that will never exit on their own — e.g. ['Application startup complete'] on a server so you know when to hit its endpoint, or ['migration done'] on a daemon. DO NOT use for: (1) end-of-run markers like 'DONE'/'PASS' — use notify_on_complete instead; (2) error patterns like 'ERROR'/'Traceback' in loops or multi-item batch jobs — they fire on every iteration and you'll hit the strike limit fast; (3) anything you'd ever combine with notify_on_complete. When in doubt, choose notify_on_complete. MUTUALLY EXCLUSIVE with notify_on_complete — set one, not both." } }, "required": [ "command" ] } } } ], "message_count": 39, "messages": [ { "role": "user", "content": "Umfassende Internet-Recherche zu aktuellen VC-Trends 2026, speziell in den Bereichen Security, KI, AI Agents, und angrenzenden Feldern. Identifiziere was VCs gerade finanzieren, welche Sektoren hot sind, welche Deal-Größen und Bewertungen üblich sind, und welche spezifischen Nischen unterversorgt oder im Hype sind. Sammle konkrete Daten: aktuelle Fundraising-Runden, VC-Thesis-Statements, Marktgrößen, und emergente Technologietrends." }, { "role": "assistant", "content": "Ich starte die Recherche. Zunächst prüfe ich den Workspace und die verfügbaren Tools für Web-Recherche.", "reasoning": "I need to conduct comprehensive internet research on current VC trends 2026, focusing on Security, AI, AI Agents, and adjacent fields. I should use web search tools if available, but I only have terminal and process tools. Let me check if there are any web search capabilities or if I need to use curl/wget to gather information.\n\nLet me start by exploring the workspace and then use terminal commands to fetch data from the web.", "finish_reason": "tool_calls", "reasoning_content": "I need to conduct comprehensive internet research on current VC trends 2026, focusing on Security, AI, AI Agents, and adjacent fields. I should use web search tools if available, but I only have terminal and process tools. Let me check if there are any web search capabilities or if I need to use curl/wget to gather information.\n\nLet me start by exploring the workspace and then use terminal commands to fetch data from the web.", "tool_calls": [ { "id": "functions.terminal:0", "call_id": "functions.terminal:0", "response_item_id": "fc_functionsterminal0", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"ls -la /DATA \\u0026\\u0026 which curl wget python3 node 2\\u003e/dev/null\",\"workdir\":\"/DATA\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"total 2672472\\ndrwxr-xr-x 28 root root 4096 Jun 10 17:00 .\\ndrwxr-xr-x 19 root root 310 Apr 21 14:30 ..\\ndrwxrwxrwx 21 root root 4096 Jun 11 09:25 AppData\\ndrwxrwxrwx 2 root root 4096 Jun 1 19:06 Backup\\n-rw-r--r-- 1 root root 65 Apr 13 01:24 .bash_profile\\n-rw-r--r-- 1 root root 6635 Apr 13 01:24 .bashrc\\ndrwxr-xr-x 6 root root 4096 Jun 2 20:15 bin\\ndrwx------ 3 root root 4096 Apr 13 01:24 .bluetooth\\ndrwxr-xr-x 9 az-a samba 4096 Jun 18 15:30 .cache\\ndrwxr-xr-x 9 root root 4096 Jun 20 09:14 .casaos\\ndrwxrwxrwx 2 root root 4096 Jun 2 16:17 .claude\\ndrwx--x--- 13 root root 4096 Jun 8 13:24 .docker\\ndrwxrwxrwx 2 root root 4096 Jun 1 19:07 Documents\\ndrwxrwxrwx 2 root root 4096 Jun 1 19:06 Downloads\\n-rwxrw-rw- 1 root root 8196 Jun 16 13:14 .DS_Store\\ndrwxr-xr-x 2 root root 4096 Jun 18 18:40 .extensions\\ndrwxrwxrwx 2 root root 4096 Jun 1 19:06 Gallery\\ndrwx------ 14 az-a samba 4096 Jun 20 09:49 .hermes\\ndrwxr-xr-x 3 root root 4096 Apr 13 01:24 .icewhale\\ndrwxr-xr-x 13 root root 4096 May 24 17:23 .libvirt\\ndrwxr-xr-x 14 az-a samba 4096 Jun 18 15:19 .local\\ndrwxr-xr-x 8 root root 4096 Apr 13 01:24 .log\\ndrwxr-xr-x 2 root root 4096 Jun 2 20:15 logs\\ndrwx------ 2 root root 16384 Apr 13 01:23 lost+found\\ndrwxr-xr-x 4 root root 4096 May 8 13:49 .media\\ndrwxr-xr-x 8 root root 4096 Apr 23 15:47 Media\\n-rw-r--r-- 1 root root 5153 Jun 4 13:11 nginxui_reddit_summary.md\\ndrwxr-xr-x 5 az-a samba 4096 Jun 1 13:31 .npm\\n-rw------- 1 root root 18725 May 2 18:19 openclaw-backup.json\\ndrwxr-xr-x 4 root root 4096 Apr 13 12:43 .opt\\ndrwxr-xr-x 4 root root 4096 Apr 21 16:00 .ota\\ndrwx------ 2 root root 4096 May 2 09:37 .ssh\\n-rw------- 1 root root 2736415744 Apr 28 10:18 .swapfile\\n-rw-r--r-- 1 root root 0 Jun 4 13:10 test.txt\\ndrwxr-xr-x 3 root root 4096 May 29 14:38 .trash\\n-rw-r--r-- 1 root root 1662 Apr 13 01:24 .wgetrc\\n/usr/bin/curl\\n/usr/bin/wget\\n/usr/bin/python3\\n/DATA/bin/node\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "functions.terminal:0" }, { "role": "assistant", "content": "Ich habe keinen direkten Webbrowser, aber ich kann mit Python/curl Webseiten abrufen und analysieren. Ich starte eine systematische Recherche mit mehreren parallelen Web-Scrapes zu den gefragten Themen.", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "functions.terminal:1", "call_id": "functions.terminal:1", "response_item_id": "fc_functionsterminal1", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"mkdir -p /DATA/research_vc_2026 \\u0026\\u0026 cd /DATA/research_vc_2026 \\u0026\\u0026 python3 - \\u003c\\u003c'PY'\\nimport json, urllib.request, urllib.error, ssl, re, sys, time\\nfrom urllib.parse import quote\\n\\nctx = ssl.create_default_context()\\nctx.check_hostname = False\\nctx.verify_mode = ssl.CERT_NONE\\n\\ndef fetch(url, headers=None, timeout=20):\\n try:\\n req = urllib.request.Request(url, headers=headers or {\\\"User-Agent\\\":\\\"Mozilla/5.0 (Windows NT 10.0; Win64; x64)\\\"})\\n with urllib.request.urlopen(req, context=ctx, timeout=timeout) as r:\\n return r.read().decode('utf-8', errors='ignore')\\n except Exception as e:\\n return f\\\"ERROR: {e}\\\"\\n\\nurls = {\\n \\\"a16z_ideas\\\": \\\"https://a16z.com/all-articles/\\\",\\n \\\"a16z_ai\\\": \\\"https://a16z.com/ai/\\\",\\n \\\"sequoia_articles\\\": \\\"https://www.sequoiacap.com/article/\\\",\\n \\\"accel_insights\\\": \\\"https://www.accel.com/insights\\\",\\n \\\"cbinsights_trends\\\": \\\"https://www.cbinsights.com/research/artificial-intelligence-trends/\\\",\\n \\\"cbinsights_ai_agents\\\": \\\"https://www.cbinsights.com/research/artificial-intelligence-agents/\\\",\\n \\\"pitchbook_vc\\\": \\\"https://pitchbook.com/news/articles/category/vc-news\\\",\\n \\\"crunchbase_ai\\\": \\\"https://news.crunchbase.com/artificial-intelligence/\\\",\\n \\\"cyberstartups_vc\\\": \\\"https://techcrunch.com/category/security/\\\",\\n \\\"wsj_vc\\\": \\\"https://www.wsj.com/tech/vc-funding\\\"\\n}\\n\\nresults = {}\\nfor name, url in urls.items():\\n print(f\\\"Fetching {name} ...\\\", file=sys.stderr)\\n html = fetch(url)\\n results[name] = {\\\"url\\\": url, \\\"len\\\": len(html), \\\"prefix\\\": html[:4000]}\\n time.sleep(0.5)\\n\\nwith open(\\\"fetches_raw.json\\\",\\\"w\\\",encoding=\\\"utf-8\\\") as f:\\n json.dump(results, f, ensure_ascii=False, indent=2)\\nprint(\\\"Done initial fetch.\\\")\\nPY\\nls -la\\n\",\"workdir\":\"/DATA/research_vc_2026\",\"timeout\":120}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"/usr/bin/bash: line 2: cd: /DATA/research_vc_2026: No such file or directory\", \"exit_code\": 126, \"error\": null}", "tool_call_id": "functions.terminal:1" }, { "role": "assistant", "content": "Der mkdir-Befehl hat wohl nicht funktioniert, da das Kommando komplex war. Ich teile es auf.", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "functions.terminal:2", "call_id": "functions.terminal:2", "response_item_id": "fc_functionsterminal2", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"mkdir -p /DATA/research_vc_2026 \\u0026\\u0026 cd /DATA/research_vc_2026 \\u0026\\u0026 pwd \\u0026\\u0026 ls -la\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"mkdir: cannot create directory ‘/DATA/research_vc_2026’: Permission denied\", \"exit_code\": 1, \"error\": null}", "tool_call_id": "functions.terminal:2" }, { "role": "assistant", "content": "Ich habe keine Schreibrechte unter /DATA. Ich prüfe, in welchem Verzeichnis ich schreiben darf, und nutze /tmp oder das home-Verzeichnis.", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "functions.terminal:3", "call_id": "functions.terminal:3", "response_item_id": "fc_functionsterminal3", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"whoami \\u0026\\u0026 id \\u0026\\u0026 pwd \\u0026\\u0026 touch /tmp/write_test \\u0026\\u0026 echo OK /tmp \\u0026\\u0026 mkdir -p /tmp/research_vc_2026 \\u0026\\u0026 cd /tmp/research_vc_2026 \\u0026\\u0026 pwd\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"az-a\\nuid=999(az-a) gid=1000(samba) groups=1000(samba),10(wheel),104(docker)\\n/DATA\\nOK /tmp\\n/tmp/research_vc_2026\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "functions.terminal:3" }, { "role": "assistant", "content": "", "reasoning": "Ich habe keine Schreibrechte direkt in /DATA, aber /tmp funktioniert. Ich werde die Recherche in /tmp/research_vc_2026 durchführen und das Ergebnis ggf. nach /DATA kopieren oder dem Boss den Pfad /tmp mitteilen. Vielleicht darf ich in ein Unterverzeichnis von /DATA schreiben, das dem Benutzer az-a gehört (z.B. /DATA/AppData). Lassen Sie mich das prüfen.\n\nIch sollte systematisch vorgehen:\n1. Prüfe Schreibrechte in /DATA Unterverzeichnissen\n2. Starte Web-Recherche mit Python urllib/curl\n3. Sammle Daten zu:\n - Aktuellen VC-Fundraising-Daten 2026\n - KI/Agenten-Startups mit großen Runden\n - Security-Startups (CrowdStrike-Markt, Supply Chain, AI Security)\n - Emerging Trends: AI Agent Infrastructure, A2A Protocols, AI Security, Agent Orchestration, Confidential Computing\n - VC-Thesen (a16z, Sequoia, Benchmark, Accel)\n - Marktgrößen\n\nDa ich keinen Browser habe, nutze ich Web-Scraping. Viele Seiten blockieren möglicherweise scraping. Ich sollte versuchen, über DuckDuckGo oder andere Suchmaschinen zu suchen, um aktuelle Artikel zu finden. Ich kann auch spezifische URLs abrufen, die ich kenne.\n\nIch werde parallel mehrere Web-Requests starten. Dann analysiere ich die Ergebnisse.", "finish_reason": "tool_calls", "reasoning_content": "Ich habe keine Schreibrechte direkt in /DATA, aber /tmp funktioniert. Ich werde die Recherche in /tmp/research_vc_2026 durchführen und das Ergebnis ggf. nach /DATA kopieren oder dem Boss den Pfad /tmp mitteilen. Vielleicht darf ich in ein Unterverzeichnis von /DATA schreiben, das dem Benutzer az-a gehört (z.B. /DATA/AppData). Lassen Sie mich das prüfen.\n\nIch sollte systematisch vorgehen:\n1. Prüfe Schreibrechte in /DATA Unterverzeichnissen\n2. Starte Web-Recherche mit Python urllib/curl\n3. Sammle Daten zu:\n - Aktuellen VC-Fundraising-Daten 2026\n - KI/Agenten-Startups mit großen Runden\n - Security-Startups (CrowdStrike-Markt, Supply Chain, AI Security)\n - Emerging Trends: AI Agent Infrastructure, A2A Protocols, AI Security, Agent Orchestration, Confidential Computing\n - VC-Thesen (a16z, Sequoia, Benchmark, Accel)\n - Marktgrößen\n\nDa ich keinen Browser habe, nutze ich Web-Scraping. Viele Seiten blockieren möglicherweise scraping. Ich sollte versuchen, über DuckDuckGo oder andere Suchmaschinen zu suchen, um aktuelle Artikel zu finden. Ich kann auch spezifische URLs abrufen, die ich kenne.\n\nIch werde parallel mehrere Web-Requests starten. Dann analysiere ich die Ergebnisse.", "tool_calls": [ { "id": "functions.terminal:4", "call_id": "functions.terminal:4", "response_item_id": "fc_functionsterminal4", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"ls -ld /DATA/AppData /DATA/Documents /DATA/Downloads 2\\u003e/dev/null \\u0026\\u0026 touch /DATA/AppData/write_test \\u0026\\u0026 echo \\\"AppData writable\\\" \\u0026\\u0026 rm /DATA/AppData/write_test\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"drwxrwxrwx 21 root root 4096 Jun 11 09:25 /DATA/AppData\\ndrwxrwxrwx 2 root root 4096 Jun 1 19:07 /DATA/Documents\\ndrwxrwxrwx 2 root root 4096 Jun 1 19:06 /DATA/Downloads\\nAppData writable\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "functions.terminal:4" }, { "role": "assistant", "content": "Ich habe Schreibrechte unter /DATA/AppData. Ich lege dort den Research-Ordner an.", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "functions.terminal:5", "call_id": "functions.terminal:5", "response_item_id": "fc_functionsterminal5", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"mkdir -p /DATA/AppData/research_vc_2026 \\u0026\\u0026 cd /DATA/AppData/research_vc_2026 \\u0026\\u0026 python3 - \\u003c\\u003c'PY'\\nimport json, urllib.request, ssl, sys, time\\n\\nctx = ssl.create_default_context()\\nctx.check_hostname = False\\nctx.verify_mode = ssl.CERT_NONE\\n\\ndef fetch(url, headers=None, timeout=25):\\n try:\\n req = urllib.request.Request(url, headers=headers or {\\\"User-Agent\\\":\\\"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 Chrome/120.0.0.0 Safari/537.36\\\",\\\"Accept\\\":\\\"text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8\\\"})\\n with urllib.request.urlopen(req, context=ctx, timeout=timeout) as r:\\n return r.read().decode('utf-8', errors='ignore')\\n except Exception as e:\\n return f\\\"ERROR: {type(e).__name__}: {e}\\\"\\n\\nurls = {\\n \\\"a16z_all\\\": \\\"https://a16z.com/all-articles/\\\",\\n \\\"a16z_ai\\\": \\\"https://a16z.com/ai/\\\",\\n \\\"sequoia_article\\\": \\\"https://www.sequoiacap.com/article/\\\",\\n \\\"sequoia_ai\\\": \\\"https://www.sequoiacap.com/article/ai/\\\",\\n \\\"accel_insights\\\": \\\"https://www.accel.com/insights\\\",\\n \\\"cbinsights_ai_trends\\\": \\\"https://www.cbinsights.com/research/artificial-intelligence-trends/\\\",\\n \\\"cbinsights_ai_agents\\\": \\\"https://www.cbinsights.com/research/artificial-intelligence-agents/\\\",\\n \\\"pitchbook_vc_news\\\": \\\"https://pitchbook.com/news/articles/category/vc-news\\\",\\n \\\"pitchbook_ai\\\": \\\"https://pitchbook.com/news/articles/artificial-intelligence\\\",\\n \\\"crunchbase_ai\\\": \\\"https://news.crunchbase.com/artificial-intelligence/\\\",\\n \\\"crunchbase_funding\\\": \\\"https://news.crunchbase.com/venture/\\\",\\n \\\"techcrunch_security\\\": \\\"https://techcrunch.com/category/security/\\\",\\n \\\"wsj_vc\\\": \\\"https://www.wsj.com/tech/vc-funding\\\",\\n \\\"fortune_term_sheet\\\": \\\"https://fortune.com/section/term-sheet/\\\",\\n \\\"theinformation_ai\\\": \\\"https://www.theinformation.com/topics/artificial-intelligence\\\",\\n \\\"bvp_cloud\\\": \\\"https://www.bvp.com/insights\\\",\\n \\\"insight_partners\\\": \\\"https://www.insightpartners.com/insights/\\\",\\n \\\"meritech_vc\\\": \\\"https://meritechcapital.com/insights/\\\",\\n \\\"cybersecurity_ventures_stats\\\": \\\"https://cybersecurityventures.com/cybercrime-damages-6-trillion-by-2021/\\\"\\n}\\n\\nresults = {}\\nfor name, url in urls.items():\\n print(f\\\"Fetching {name} ...\\\", file=sys.stderr)\\n html = fetch(url)\\n results[name] = {\\\"url\\\": url, \\\"len\\\": len(html), \\\"prefix\\\": html[:5000], \\\"error\\\": html if html.startswith(\\\"ERROR\\\") else None}\\n time.sleep(0.7)\\n\\nwith open(\\\"fetches_raw_1.json\\\",\\\"w\\\",encoding=\\\"utf-8\\\") as f:\\n json.dump(results, f, ensure_ascii=False, indent=2)\\nprint(\\\"Done batch 1.\\\")\\nPY\\nls -la\\n\",\"timeout\":180,\"workdir\":\"/DATA/AppData/research_vc_2026\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"/usr/bin/bash: line 2: cd: /DATA/AppData/research_vc_2026: No such file or directory\", \"exit_code\": 126, \"error\": null}", "tool_call_id": "functions.terminal:5" }, { "role": "assistant", "content": "Es gibt ein Problem mit der Shell-Interpretation des kombinierten Befehls. Ich führe mkdir und Python in separaten Schritten aus.", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "functions.terminal:6", "call_id": "functions.terminal:6", "response_item_id": "fc_functionsterminal6", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"mkdir -p /DATA/AppData/research_vc_2026 \\u0026\\u0026 pwd \\u0026\\u0026 ls -la /DATA/AppData/research_vc_2026\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"/tmp/research_vc_2026\\ntotal 8\\ndrwxr-xr-x 2 az-a samba 4096 Jun 20 09:49 .\\ndrwxrwxrwx 22 root root 4096 Jun 20 09:49 ..\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "functions.terminal:6" }, { "role": "assistant", "content": "", "reasoning": "Der Ordner ist jetzt da. Ich wechsle in einen klaren Arbeitsschritt.", "finish_reason": "tool_calls", "reasoning_content": "Der Ordner ist jetzt da. Ich wechsle in einen klaren Arbeitsschritt.", "tool_calls": [ { "id": "functions.terminal:7", "call_id": "functions.terminal:7", "response_item_id": "fc_functionsterminal7", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"cd /DATA/AppData/research_vc_2026 \\u0026\\u0026 python3 - \\u003c\\u003c'PY'\\nimport json, urllib.request, ssl, sys, time\\n\\nctx = ssl.create_default_context()\\nctx.check_hostname = False\\nctx.verify_mode = ssl.CERT_NONE\\n\\ndef fetch(url, headers=None, timeout=25):\\n try:\\n req = urllib.request.Request(url, headers=headers or {\\\"User-Agent\\\":\\\"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 Chrome/120.0.0.0 Safari/537.36\\\",\\\"Accept\\\":\\\"text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8\\\"})\\n with urllib.request.urlopen(req, context=ctx, timeout=timeout) as r:\\n return r.read().decode('utf-8', errors='ignore')\\n except Exception as e:\\n return f\\\"ERROR: {type(e).__name__}: {e}\\\"\\n\\nurls = {\\n \\\"a16z_all\\\": \\\"https://a16z.com/all-articles/\\\",\\n \\\"a16z_ai\\\": \\\"https://a16z.com/ai/\\\",\\n \\\"sequoia_article\\\": \\\"https://www.sequoiacap.com/article/\\\",\\n \\\"sequoia_ai\\\": \\\"https://www.sequoiacap.com/article/ai/\\\",\\n \\\"accel_insights\\\": \\\"https://www.accel.com/insights\\\",\\n \\\"cbinsights_ai_trends\\\": \\\"https://www.cbinsights.com/research/artificial-intelligence-trends/\\\",\\n \\\"cbinsights_ai_agents\\\": \\\"https://www.cbinsights.com/research/artificial-intelligence-agents/\\\",\\n \\\"pitchbook_vc_news\\\": \\\"https://pitchbook.com/news/articles/category/vc-news\\\",\\n \\\"pitchbook_ai\\\": \\\"https://pitchbook.com/news/articles/artificial-intelligence\\\",\\n \\\"crunchbase_ai\\\": \\\"https://news.crunchbase.com/artificial-intelligence/\\\",\\n \\\"crunchbase_funding\\\": \\\"https://news.crunchbase.com/venture/\\\",\\n \\\"techcrunch_security\\\": \\\"https://techcrunch.com/category/security/\\\",\\n \\\"wsj_vc\\\": \\\"https://www.wsj.com/tech/vc-funding\\\",\\n \\\"fortune_term_sheet\\\": \\\"https://fortune.com/section/term-sheet/\\\",\\n \\\"bvp_cloud\\\": \\\"https://www.bvp.com/insights\\\",\\n \\\"insight_partners\\\": \\\"https://www.insightpartners.com/insights/\\\",\\n \\\"meritech_vc\\\": \\\"https://meritechcapital.com/insights/\\\",\\n \\\"cybersecurity_ventures_stats\\\": \\\"https://cybersecurityventures.com/cybercrime-damages-6-trillion-by-2021/\\\",\\n \\\"gartner_ai_software\\\": \\\"https://www.gartner.com/en/articles/ai-software-market-forecast\\\",\\n \\\"mckinsey_state_of_ai\\\": \\\"https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai\\\"\\n}\\n\\nresults = {}\\nfor name, url in urls.items():\\n print(f\\\"Fetching {name} ...\\\", file=sys.stderr)\\n html = fetch(url)\\n results[name] = {\\\"url\\\": url, \\\"len\\\": len(html), \\\"error\\\": html if html.startswith(\\\"ERROR\\\") else None, \\\"prefix\\\": html[:6000]}\\n time.sleep(0.8)\\n\\nwith open(\\\"fetches_raw_1.json\\\",\\\"w\\\",encoding=\\\"utf-8\\\") as f:\\n json.dump(results, f, ensure_ascii=False, indent=2)\\nprint(\\\"Done batch 1.\\\")\\nPY\\nls -la\\n\",\"timeout\":300,\"workdir\":\"/DATA/AppData/research_vc_2026\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"Fetching a16z_all ...\\nFetching a16z_ai ...\\nFetching sequoia_article ...\\nFetching sequoia_ai ...\\nFetching accel_insights ...\\nFetching cbinsights_ai_trends ...\\nFetching cbinsights_ai_agents ...\\nFetching pitchbook_vc_news ...\\nFetching pitchbook_ai ...\\nFetching crunchbase_ai ...\\nFetching crunchbase_funding ...\\nFetching techcrunch_security ...\\nFetching wsj_vc ...\\nFetching fortune_term_sheet ...\\nFetching bvp_cloud ...\\nFetching insight_partners ...\\nFetching meritech_vc ...\\nFetching cybersecurity_ventures_stats ...\\nFetching gartner_ai_software ...\\nFetching mckinsey_state_of_ai ...\\nDone batch 1.\\ntotal 56\\ndrwxr-xr-x 2 az-a samba 4096 Jun 20 09:50 .\\ndrwxrwxrwx 22 root root 4096 Jun 20 09:49 ..\\n-rw-r--r-- 1 az-a samba 48596 Jun 20 09:50 fetches_raw_1.json\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "functions.terminal:7" }, { "role": "assistant", "content": "Die ersten Fetches sind gespeichert. Jetzt analysiere ich, welche Quellen funktioniert haben, und führe weitere gezielte Recherchen durch.", "reasoning": "", "finish_reason": "tool_calls", "reasoning_content": "", "tool_calls": [ { "id": "functions.terminal:8", "call_id": "functions.terminal:8", "response_item_id": "fc_functionsterminal8", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"cd /DATA/AppData/research_vc_2026 \\u0026\\u0026 python3 - \\u003c\\u003c'PY'\\nimport json\\nwith open(\\\"fetches_raw_1.json\\\") as f:\\n data=json.load(f)\\nfor k,v in data.items():\\n print(f\\\"{k:25s} len={v['len']:7d} err={'YES' if v['error'] else 'NO'}\\\")\\nPY\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"a16z_all len= 43 err=YES\\na16z_ai len= 832457 err=NO\\nsequoia_article len= 43 err=YES\\nsequoia_ai len= 43 err=YES\\naccel_insights len= 508338 err=NO\\ncbinsights_ai_trends len= 121932 err=NO\\ncbinsights_ai_agents len= 121932 err=NO\\npitchbook_vc_news len= 43 err=YES\\npitchbook_ai len= 43 err=YES\\ncrunchbase_ai len= 43 err=YES\\ncrunchbase_funding len= 174365 err=NO\\ntechcrunch_security len= 305183 err=NO\\nwsj_vc len= 48 err=YES\\nfortune_term_sheet len= 43 err=YES\\nbvp_cloud len= 43 err=YES\\ninsight_partners len= 43 err=YES\\nmeritech_vc len= 43 err=YES\\ncybersecurity_ventures_stats len= 195309 err=NO\\ngartner_ai_software len= 43 err=YES\\nmckinsey_state_of_ai len= 49 err=YES\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "functions.terminal:8" }, { "role": "assistant", "content": "", "reasoning": "Viele Seiten blockieren einfachen Python-urllib-Zugriff. Ich werde curl mit zusätzlichen Headern und evtl. über DuckDuckGo/Bing als Suchmaschinen-Proxy testen. Eine gute Strategie: Google-Suchergebnisse via html.duckduckgo.com oder bing.com/news. Außerdem kann ich direkt News-Artikel abrufen, die oft weniger Cloudflare-Schutz haben. \n\nPlan:\n1. Curl-Test auf einige der blockierten Seiten.\n2. Suche nach aktuellen Funding-Runden via DuckDuckGo/Crunchbase-API? Ohne API-Key schwierig.\n3. Suche nach \"largest AI funding rounds 2026\", \"AI agents funding 2026\", \"cybersecurity startup funding 2026\", \"VC trends 2026\".\n4. Suche nach spezifischen Seiten wie TechCrunch-Artikeln, The Verge, Reuters.\n5. a16z AI-Seite hat funktioniert -> parse Inhalte.\n6. CB Insights hat funktioniert -> parse.\n7. Accel Insights hat funktioniert -> parse.\n8. TechCrunch Security hat funktioniert -> parse.\n9. Crunchbase funding hat funktioniert -> parse.\n10. Cybersecurity Ventures hat funktioniert -> parse.\n\nIch sollte auch gezielt nach Marktgrößen suchen: Gartner, IDC, McKinsey. Stattdessen kann ich Wikipedia/Statista-ähnliche Seiten oder Research-Berichte (z.B. Bessemer) abrufen.\n\nIch starte weitere Fetches mit curl, da curl oft akzeptierter ist.", "finish_reason": "tool_calls", "reasoning_content": "Viele Seiten blockieren einfachen Python-urllib-Zugriff. Ich werde curl mit zusätzlichen Headern und evtl. über DuckDuckGo/Bing als Suchmaschinen-Proxy testen. Eine gute Strategie: Google-Suchergebnisse via html.duckduckgo.com oder bing.com/news. Außerdem kann ich direkt News-Artikel abrufen, die oft weniger Cloudflare-Schutz haben. \n\nPlan:\n1. Curl-Test auf einige der blockierten Seiten.\n2. Suche nach aktuellen Funding-Runden via DuckDuckGo/Crunchbase-API? Ohne API-Key schwierig.\n3. Suche nach \"largest AI funding rounds 2026\", \"AI agents funding 2026\", \"cybersecurity startup funding 2026\", \"VC trends 2026\".\n4. Suche nach spezifischen Seiten wie TechCrunch-Artikeln, The Verge, Reuters.\n5. a16z AI-Seite hat funktioniert -> parse Inhalte.\n6. CB Insights hat funktioniert -> parse.\n7. Accel Insights hat funktioniert -> parse.\n8. TechCrunch Security hat funktioniert -> parse.\n9. Crunchbase funding hat funktioniert -> parse.\n10. Cybersecurity Ventures hat funktioniert -> parse.\n\nIch sollte auch gezielt nach Marktgrößen suchen: Gartner, IDC, McKinsey. Stattdessen kann ich Wikipedia/Statista-ähnliche Seiten oder Research-Berichte (z.B. Bessemer) abrufen.\n\nIch starte weitere Fetches mit curl, da curl oft akzeptierter ist.", "tool_calls": [ { "id": "functions.terminal:9", "call_id": "functions.terminal:9", "response_item_id": "fc_functionsterminal9", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"cd /DATA/AppData/research_vc_2026 \\u0026\\u0026 curl -L -s -A \\\"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 Chrome/120.0.0.0 Safari/537.36\\\" -o test_a16z.html https://a16z.com/all-articles/ \\u0026\\u0026 wc -c test_a16z.html \\u0026\\u0026 head -c 500 test_a16z.html\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"126774 test_a16z.html\\n\\n\\n\\n\\n\\n\\n\\n \\n \\n \\n \\n \\n Page not found | Andreessen Horowitz\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "functions.terminal:9" }, { "role": "assistant", "content": "", "reasoning": "Der Pfad /all-articles/ scheint bei a16z nicht mehr zu existieren. Die Hauptseite /ai/ hat aber funktioniert. Ich muss also bessere URLs finden. Ich nutze gezielt a16z.com/ai, a16z.com/2026 etc. und versuche weitere Quellen.", "finish_reason": "tool_calls", "reasoning_content": "Der Pfad /all-articles/ scheint bei a16z nicht mehr zu existieren. Die Hauptseite /ai/ hat aber funktioniert. Ich muss also bessere URLs finden. Ich nutze gezielt a16z.com/ai, a16z.com/2026 etc. und versuche weitere Quellen.", "tool_calls": [ { "id": "functions.terminal:10", "call_id": "functions.terminal:10", "response_item_id": "fc_functionsterminal10", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"cd /DATA/AppData/research_vc_2026 \\u0026\\u0026 curl -L -s -A \\\"Mozilla/5.0\\\" -o test_a16z_ai.html https://a16z.com/ai/ \\u0026\\u0026 wc -c test_a16z_ai.html \\u0026\\u0026 grep -oE '\\u003ctitle\\u003e[^\\u003c]+\\u003c/title\\u003e' test_a16z_ai.html \\u0026\\u0026 grep -oE 'meta name=\\\"description\\\" content=\\\"[^\\\"]+\\\"' test_a16z_ai.html | head -3\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"832457 test_a16z_ai.html\\nAI a16z | Andreessen Horowitz\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "functions.terminal:10" }, { "role": "assistant", "content": "", "reasoning": "We can see a16z/ai works. Need to parse content. Many sites like WSJ require JS/login. I can still extract visible text from HTML. Let's run targeted content extraction using Python BeautifulSoup if installed.", "finish_reason": "tool_calls", "reasoning_content": "We can see a16z/ai works. Need to parse content. Many sites like WSJ require JS/login. I can still extract visible text from HTML. Let's run targeted content extraction using Python BeautifulSoup if installed.", "tool_calls": [ { "id": "functions.terminal:11", "call_id": "functions.terminal:11", "response_item_id": "fc_functionsterminal11", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"cd /DATA/AppData/research_vc_2026 \\u0026\\u0026 python3 -c \\\"import bs4; print(bs4.__version__)\\\" 2\\u003e/dev/null || pip3 install beautifulsoup4 lxml -q\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"4.14.3\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "functions.terminal:11" }, { "role": "assistant", "content": "", "reasoning": "We need do extensive research. Need use web. Could use a headless browser? Probably not installed. We can use python requests to fetch pages and parse. We have beautifulsoup. Need gather data points. Could also use news sites. We can search via duckduckgo or google search? We don't have API. But can use search engines with query in URL maybe returns results. DuckDuckGo HTML search can be scraped with q parameter: https://html.duckduckgo.com/html/?q=... It returns search results. Use that. Let's query various topics: VC trends 2026, AI agent funding rounds 2026, cybersecurity startup funding 2026, etc. We can collect results. Also use Crunchbase, PitchBook, TechCrunch. We'll use a16z AI page content, Accel insights, CB Insights pages, cybersecurityventures, etc. Use search for specific data: \"AI agent funding 2026\", \"2026 venture capital AI security\", \"a16z AI thesis 2026\", \"Sequoia AI agents 2026\", \"Benchmark AI agents 2026\", \"CB Insights State of Venture 2026\", \"PitchBook venture monitor Q1 2026\", \"Gartner AI software spending 2026\", \"cybersecurity market size 2026\", \"CrowdStrike market share\". Let's do many search queries and collect snippets/links. Then fetch key pages. Use Python to query duckduckgo. Be careful rate. Could be blocked. Use random sleep. We can also use Bing? Bing search no API. DuckDuckGo html can work with proper UA. Let's implement robust. Also maybe use Brave search? Not. We'll attempt. Use requests maybe better. urllib ok. Let's create script.\n\nNeed avoid overly long outputs. We'll save all data into files. We'll need generate final structured brief in German. We don't need include every raw file in summary, just list file path.\n\nLet's proceed with broad search.", "finish_reason": "tool_calls", "reasoning_content": "We need do extensive research. Need use web. Could use a headless browser? Probably not installed. We can use python requests to fetch pages and parse. We have beautifulsoup. Need gather data points. Could also use news sites. We can search via duckduckgo or google search? We don't have API. But can use search engines with query in URL maybe returns results. DuckDuckGo HTML search can be scraped with q parameter: https://html.duckduckgo.com/html/?q=... It returns search results. Use that. Let's query various topics: VC trends 2026, AI agent funding rounds 2026, cybersecurity startup funding 2026, etc. We can collect results. Also use Crunchbase, PitchBook, TechCrunch. We'll use a16z AI page content, Accel insights, CB Insights pages, cybersecurityventures, etc. Use search for specific data: \"AI agent funding 2026\", \"2026 venture capital AI security\", \"a16z AI thesis 2026\", \"Sequoia AI agents 2026\", \"Benchmark AI agents 2026\", \"CB Insights State of Venture 2026\", \"PitchBook venture monitor Q1 2026\", \"Gartner AI software spending 2026\", \"cybersecurity market size 2026\", \"CrowdStrike market share\". Let's do many search queries and collect snippets/links. Then fetch key pages. Use Python to query duckduckgo. Be careful rate. Could be blocked. Use random sleep. We can also use Bing? Bing search no API. DuckDuckGo html can work with proper UA. Let's implement robust. Also maybe use Brave search? Not. We'll attempt. Use requests maybe better. urllib ok. Let's create script.\n\nNeed avoid overly long outputs. We'll save all data into files. We'll need generate final structured brief in German. We don't need include every raw file in summary, just list file path.\n\nLet's proceed with broad search.", "tool_calls": [ { "id": "functions.terminal:12", "call_id": "functions.terminal:12", "response_item_id": "fc_functionsterminal12", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"cd /DATA/AppData/research_vc_2026 \\u0026\\u0026 python3 - \\u003c\\u003c'PY'\\nimport json, urllib.request, ssl, time, re, html\\nfrom bs4 import BeautifulSoup\\n\\nctx = ssl.create_default_context()\\nctx.check_hostname = False\\nctx.verify_mode = ssl.CERT_NONE\\n\\ndef fetch(url, headers=None, timeout=25):\\n try:\\n req = urllib.request.Request(url, headers=headers or {\\\"User-Agent\\\":\\\"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 Chrome/120.0.0.0 Safari/537.36\\\",\\\"Accept\\\":\\\"text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8\\\"})\\n with urllib.request.urlopen(req, context=ctx, timeout=timeout) as r:\\n return r.read().decode('utf-8', errors='ignore')\\n except Exception as e:\\n return f\\\"ERROR: {type(e).__name__}: {e}\\\"\\n\\ndef ddg_search(query, num=10):\\n url = \\\"https://html.duckduckgo.com/html/?q=\\\" + urllib.parse.quote(query)\\n h = fetch(url, timeout=30)\\n if h.startswith(\\\"ERROR\\\"):\\n return []\\n soup = BeautifulSoup(h, \\\"html.parser\\\")\\n res=[]\\n for r in soup.select(\\\".result\\\"):\\n a = r.select_one(\\\".result__a\\\")\\n if not a: continue\\n title = a.get_text(strip=True)\\n link = a.get(\\\"href\\\",\\\"\\\")\\n snippet_el = r.select_one(\\\".result__snippet\\\")\\n snippet = snippet_el.get_text(strip=True) if snippet_el else \\\"\\\"\\n res.append({\\\"title\\\":title,\\\"link\\\":link,\\\"snippet\\\":snippet})\\n if len(res)\\u003e=num: break\\n return res\\n\\nqueries = [\\n \\\"VC trends 2026 funding AI agents security\\\",\\n \\\"2026 AI agent startups venture capital funding rounds\\\",\\n \\\"2026 cybersecurity startups VC funding rounds valuations\\\",\\n \\\"a16z AI agent thesis 2026\\\",\\n \\\"Sequoia AI agents 2026\\\",\\n \\\"Benchmark AI agents 2026\\\",\\n \\\"Accel AI agents security 2026\\\",\\n \\\"CB Insights State of Venture 2026 report\\\",\\n \\\"PitchBook NVCA venture monitor Q1 2026\\\",\\n \\\"AI security startups VC funding 2026 prompt injection\\\",\\n \\\"confidential computing AI startups VC 2026\\\",\\n \\\"agent to agent protocol A2A VC funding\\\",\\n \\\"2026 venture capital deal sizes valuations AI\\\",\\n \\\"CrowdStrike market size cybersecurity TAM 2026\\\",\\n \\\"Gartner AI software market forecast 2026 spending\\\",\\n \\\"McKinsey state of AI 2026 report\\\",\\n \\\"AI infrastructure startups funding 2026\\\",\\n \\\"vertical AI agents enterprise funding 2026\\\",\\n \\\"supply chain security startup funding 2026\\\",\\n \\\"SaaS AI agent orchestration funding 2026\\\"\\n]\\n\\nall_results = {}\\nfor q in queries:\\n print(f\\\"DDG: {q}\\\", flush=True)\\n all_results[q] = ddg_search(q, num=12)\\n print(f\\\" -\\u003e {len(all_results[q])} results\\\")\\n time.sleep(2.5)\\n\\nwith open(\\\"ddg_search_results.json\\\",\\\"w\\\",encoding=\\\"utf-8\\\") as f:\\n json.dump(all_results, f, ensure_ascii=False, indent=2)\\nprint(\\\"DDG search done.\\\")\\nPY\\nwc -c ddg_search_results.json\\n\",\"timeout\":300,\"workdir\":\"/DATA/AppData/research_vc_2026\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"DDG: VC trends 2026 funding AI agents security\\n -> 10 results\\nDDG: 2026 AI agent startups venture capital funding rounds\\n -> 10 results\\nDDG: 2026 cybersecurity startups VC funding rounds valuations\\n -> 0 results\\nDDG: a16z AI agent thesis 2026\\n -> 0 results\\nDDG: Sequoia AI agents 2026\\n -> 0 results\\nDDG: Benchmark AI agents 2026\\n -> 0 results\\nDDG: Accel AI agents security 2026\\n -> 0 results\\nDDG: CB Insights State of Venture 2026 report\\n -> 0 results\\nDDG: PitchBook NVCA venture monitor Q1 2026\\n -> 0 results\\nDDG: AI security startups VC funding 2026 prompt injection\\n -> 0 results\\nDDG: confidential computing AI startups VC 2026\\n -> 0 results\\nDDG: agent to agent protocol A2A VC funding\\n -> 0 results\\nDDG: 2026 venture capital deal sizes valuations AI\\n -> 0 results\\nDDG: CrowdStrike market size cybersecurity TAM 2026\\n -> 0 results\\nDDG: Gartner AI software market forecast 2026 spending\\n -> 0 results\\nDDG: McKinsey state of AI 2026 report\\n -> 0 results\\nDDG: AI infrastructure startups funding 2026\\n -> 0 results\\nDDG: vertical AI agents enterprise funding 2026\\n -> 0 results\\nDDG: supply chain security startup funding 2026\\n -> 0 results\\nDDG: SaaS AI agent orchestration funding 2026\\n -> 0 results\\nDDG search done.\\n11869 ddg_search_results.json\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "functions.terminal:12" }, { "role": "assistant", "content": "", "reasoning": "DuckDuckGo html hat nach der ersten Anfrage offenbar blockiert/keine Ergebnisse mehr geliefert. Ich brauche eine andere Strategie: direkte Webseiten-Scrapes von spezifischen Artikeln, die ich kenne, oder Suche über andere Endpunkte. Ich sollte die erfolgreichen fetches aus batch 1 auswerten und mehr relevante Seiten direkt abrufen. Außerdem kann ich News-Aggregatoren verwenden, z.B. TechCrunch, VentureBeat, The Information ist aber paywall. Ich kann auch die OpenAI/Anthropic/Gemini API? Nein, keine Keys. Ich kann aber öffentliche Datenquellen nutzen: Crunchbase News (hat funktioniert), CB Insights (hat funktioniert), a16z AI (hat funktioniert), Accel Insights (hat funktioniert), Cybersecurity Ventures (hat funktioniert), TechCrunch Security (hat funktioniert), Crunchbase Funding (hat funktioniert). \n\nAuch: ich kann direkt auf bekannte Artikel URLs zugreifen, z.B. a16z \"The Unbundling of AI: Infrastructure, Agents, and Applications\", Sequoia \"AI's $600B Question\" etc. Ich kenne einige URLs aus dem Wissenscutoff; aber ich habe Zugriff auf das Internet, also kann ich sie abrufen. Lass mich systematisch die bereits gescrapten Inhalte parsen und relevante Links/Text extrahieren, dann weitere Artikel fetchen.\n\nIch habe keinen Browser, aber curl/Python reichen. Ich muss realistisch sein: viele Sites (WSJ, PitchBook, Crunchbase News manchmal) blockieren. Ich kann aber ausreichend Informationen sammeln.\n\nDer Output muss ein strukturierter Research-Brief auf Deutsch sein, ohne Startup-Ideen. Ich muss ihn in /DATA/AppData/research_vc_2026/research_brief_vc_2026.md speichern.\n\nIch werde jetzt:\n1. Aus den erfolgreichen Fetches relevante Daten extrahieren (Titel, Links, Snippets, Zahlen).\n2. Direkt einige bekannte Artikel/Reports fetchen:\n - a16z AI / articles\n - a16z \"AI Enterprise 2025\" maybe\n - Sequoia \"AI's $600B Question\" etc. via known URLs\n - CB Insights State of Venture Q1 2025/2026 report PDF? vielleicht summary page\n - PitchBook NVCA Venture Monitor report (PDFs verfügbar)\n - TechCrunch Security recent funding articles\n - Crunchbase News AI funding\n - Cybersecurity Ventures 2025/2026 reports\n - Gartner market forecasts via press releases\n - McKinsey state of AI via summary\n - \"Agent to agent protocol\" / Anthropic Model Context Protocol etc.\n3. Suche nach spezifischen Funding-Runden. Hierfür eignet sich Crunchbase News und TechCrunch.\n\nIch muss aufpassen, dass ich nicht Halluzinationen produziere. Wenn Daten nicht verfügbar, muss ich es kennzeichnen. Ich kann aber wahrscheinlich echte Daten finden.\n\nLass mich zunächst die erfolgreichen HTMLs parsen.", "finish_reason": "tool_calls", "reasoning_content": "DuckDuckGo html hat nach der ersten Anfrage offenbar blockiert/keine Ergebnisse mehr geliefert. Ich brauche eine andere Strategie: direkte Webseiten-Scrapes von spezifischen Artikeln, die ich kenne, oder Suche über andere Endpunkte. Ich sollte die erfolgreichen fetches aus batch 1 auswerten und mehr relevante Seiten direkt abrufen. Außerdem kann ich News-Aggregatoren verwenden, z.B. TechCrunch, VentureBeat, The Information ist aber paywall. Ich kann auch die OpenAI/Anthropic/Gemini API? Nein, keine Keys. Ich kann aber öffentliche Datenquellen nutzen: Crunchbase News (hat funktioniert), CB Insights (hat funktioniert), a16z AI (hat funktioniert), Accel Insights (hat funktioniert), Cybersecurity Ventures (hat funktioniert), TechCrunch Security (hat funktioniert), Crunchbase Funding (hat funktioniert). \n\nAuch: ich kann direkt auf bekannte Artikel URLs zugreifen, z.B. a16z \"The Unbundling of AI: Infrastructure, Agents, and Applications\", Sequoia \"AI's $600B Question\" etc. Ich kenne einige URLs aus dem Wissenscutoff; aber ich habe Zugriff auf das Internet, also kann ich sie abrufen. Lass mich systematisch die bereits gescrapten Inhalte parsen und relevante Links/Text extrahieren, dann weitere Artikel fetchen.\n\nIch habe keinen Browser, aber curl/Python reichen. Ich muss realistisch sein: viele Sites (WSJ, PitchBook, Crunchbase News manchmal) blockieren. Ich kann aber ausreichend Informationen sammeln.\n\nDer Output muss ein strukturierter Research-Brief auf Deutsch sein, ohne Startup-Ideen. Ich muss ihn in /DATA/AppData/research_vc_2026/research_brief_vc_2026.md speichern.\n\nIch werde jetzt:\n1. Aus den erfolgreichen Fetches relevante Daten extrahieren (Titel, Links, Snippets, Zahlen).\n2. Direkt einige bekannte Artikel/Reports fetchen:\n - a16z AI / articles\n - a16z \"AI Enterprise 2025\" maybe\n - Sequoia \"AI's $600B Question\" etc. via known URLs\n - CB Insights State of Venture Q1 2025/2026 report PDF? vielleicht summary page\n - PitchBook NVCA Venture Monitor report (PDFs verfügbar)\n - TechCrunch Security recent funding articles\n - Crunchbase News AI funding\n - Cybersecurity Ventures 2025/2026 reports\n - Gartner market forecasts via press releases\n - McKinsey state of AI via summary\n - \"Agent to agent protocol\" / Anthropic Model Context Protocol etc.\n3. Suche nach spezifischen Funding-Runden. Hierfür eignet sich Crunchbase News und TechCrunch.\n\nIch muss aufpassen, dass ich nicht Halluzinationen produziere. Wenn Daten nicht verfügbar, muss ich es kennzeichnen. Ich kann aber wahrscheinlich echte Daten finden.\n\nLass mich zunächst die erfolgreichen HTMLs parsen.", "tool_calls": [ { "id": "functions.terminal:13", "call_id": "functions.terminal:13", "response_item_id": "fc_functionsterminal13", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"cd /DATA/AppData/research_vc_2026 \\u0026\\u0026 python3 - \\u003c\\u003c'PY'\\nimport json, re\\nfrom bs4 import BeautifulSoup\\n\\nwith open(\\\"fetches_raw_1.json\\\") as f:\\n data=json.load(f)\\n\\nextracts={}\\nfor name,v in data.items():\\n if v['error'] or v['len']\\u003c5000:\\n continue\\n html=v['prefix']+v.get('body','')\\n soup=BeautifulSoup(html,'html.parser')\\n title=soup.title.string if soup.title else ''\\n meta=soup.find('meta',attrs={'name':'description'})\\n desc=meta['content'] if meta else ''\\n links=[]\\n for a in soup.find_all('a',href=True):\\n t=' '.join(a.get_text().split())[:120]\\n if t and ('AI' in t or 'agent' in t.lower() or 'security' in t.lower() or 'venture' in t.lower() or 'fund' in t.lower() or '2026' in t or '2025' in t):\\n links.append({'text':t,'href':a['href']})\\n extracts[name]={'title':title,'desc':desc,'links':links[:30]}\\n\\nwith open(\\\"extracts_1.json\\\",\\\"w\\\",encoding=\\\"utf-8\\\") as f:\\n json.dump(extracts,f,ensure_ascii=False,indent=2)\\n\\nfor k,v in extracts.items():\\n print(f\\\"--- {k} ---\\\")\\n print(v['title'])\\n print(v['desc'][:200])\\n for l in v['links'][:8]:\\n print(f\\\" {l['text'][:80]} | {l['href'][:80]}\\\")\\nPY\",\"timeout\":120,\"workdir\":\"/DATA/AppData/research_vc_2026\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"--- a16z_ai ---\\nAI a16z | Andreessen Horowitz\\n\\n--- accel_insights ---\\nAccel | Insights — Accel\\nInsights from Accel — research, analysis, and perspectives.\\n--- cbinsights_ai_trends ---\\nCB Insights Research\\n\\n--- cbinsights_ai_agents ---\\nCB Insights Research\\n\\n--- crunchbase_funding ---\\nVenture Archives - Crunchbase News\\n\\n--- techcrunch_security ---\\nSecurity News | TechCrunch\\nRead the latest news and investigative reporting on security today, including cybersecurity, breaches, hacks and cyberattacks around the globe.\\n--- cybersecurity_ventures_stats ---\\nCybercrime To Cost The World $10.5 Trillion Annually By 2025\\nSpecial Report: Cyberwarfare In The C-Suite.\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "functions.terminal:13" }, { "role": "assistant", "content": "", "reasoning": "Die bisherigen Scrapes waren wenig ergiebig, weil viele Seiten Cloudflare/JS-Blocker haben oder die a16z-URL umgeleitet wird. Ich muss gezieltere Methoden nutzen. Da ich keinen echten Browser habe, kann ich versuchen:\n1. Sitemap/RSS-Feeds abzurufen (oft weniger blockiert)\n2. Direkt PDF-Reports von CB Insights/PitchBook via Suchergebnissen zu finden\n3. News-Artikel über Crunchbase/TechCrunch/Reuters/Bloomberg\n4. VC-Firmen-Blogs via RSS\n5. Google-Suche funktioniert oft besser, aber ich muss Parameter setzen\n\nIch habe einen DDG-Block bemerkt (nach erstem Query 0 Ergebnisse). Das ist ein Rate-Limit. Ich sollte langsamer werden oder alternative Suchmaschinen verwenden. \n\nLassen Sie mich gezielt einzelne URLs abrufen, die ich aus dem Web kenne, und RSS-Feeds verwenden. Ich werde auch versuchen, Bing/SearXNG-Instanzen oder direct search queries zu nutzen.\n\nWichtige Quellen:\n- TechCrunch security\n- Crunchbase News\n- a16z RSS: https://a16z.com/feed/\n- Sequoia RSS: https://www.sequoiacap.com/feed/\n- Accel RSS\n- CB Insights Research Direct PDFs\n- PitchBook Reports (oft Paywall)\n- Bessemer VP State of Cloud\n- Meritech KBCM SaaS metrics\n\nIch muss auch nach konkreten Deals suchen:\n- Anthropic, OpenAI, xAI Runden 2025/2026\n- Cursor/Windsurf, Sierra, Adept, etc.\n- Security: Wiz, CrowdStrike, Zscaler, Island, Protect AI, HiddenLayer, etc.\n\nIch führe nun gezieltere Fetches durch, inklusive RSS und bekannte Research-URLs.", "finish_reason": "tool_calls", "reasoning_content": "Die bisherigen Scrapes waren wenig ergiebig, weil viele Seiten Cloudflare/JS-Blocker haben oder die a16z-URL umgeleitet wird. Ich muss gezieltere Methoden nutzen. Da ich keinen echten Browser habe, kann ich versuchen:\n1. Sitemap/RSS-Feeds abzurufen (oft weniger blockiert)\n2. Direkt PDF-Reports von CB Insights/PitchBook via Suchergebnissen zu finden\n3. News-Artikel über Crunchbase/TechCrunch/Reuters/Bloomberg\n4. VC-Firmen-Blogs via RSS\n5. Google-Suche funktioniert oft besser, aber ich muss Parameter setzen\n\nIch habe einen DDG-Block bemerkt (nach erstem Query 0 Ergebnisse). Das ist ein Rate-Limit. Ich sollte langsamer werden oder alternative Suchmaschinen verwenden. \n\nLassen Sie mich gezielt einzelne URLs abrufen, die ich aus dem Web kenne, und RSS-Feeds verwenden. Ich werde auch versuchen, Bing/SearXNG-Instanzen oder direct search queries zu nutzen.\n\nWichtige Quellen:\n- TechCrunch security\n- Crunchbase News\n- a16z RSS: https://a16z.com/feed/\n- Sequoia RSS: https://www.sequoiacap.com/feed/\n- Accel RSS\n- CB Insights Research Direct PDFs\n- PitchBook Reports (oft Paywall)\n- Bessemer VP State of Cloud\n- Meritech KBCM SaaS metrics\n\nIch muss auch nach konkreten Deals suchen:\n- Anthropic, OpenAI, xAI Runden 2025/2026\n- Cursor/Windsurf, Sierra, Adept, etc.\n- Security: Wiz, CrowdStrike, Zscaler, Island, Protect AI, HiddenLayer, etc.\n\nIch führe nun gezieltere Fetches durch, inklusive RSS und bekannte Research-URLs.", "tool_calls": [ { "id": "functions.terminal:14", "call_id": "functions.terminal:14", "response_item_id": "fc_functionsterminal14", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"cd /DATA/AppData/research_vc_2026 \\u0026\\u0026 python3 - \\u003c\\u003c'PY'\\nimport json, urllib.request, ssl, time, re\\nfrom bs4 import BeautifulSoup\\n\\nctx = ssl.create_default_context()\\nctx.check_hostname = False\\nctx.verify_mode = ssl.CERT_NONE\\n\\ndef fetch(url, headers=None, timeout=30):\\n try:\\n req = urllib.request.Request(url, headers=headers or {\\\"User-Agent\\\":\\\"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 Chrome/120.0.0.0 Safari/537.36\\\",\\\"Accept\\\":\\\"text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8\\\"})\\n with urllib.request.urlopen(req, context=ctx, timeout=timeout) as r:\\n return r.read().decode('utf-8', errors='ignore')\\n except Exception as e:\\n return f\\\"ERROR: {type(e).__name__}: {e}\\\"\\n\\nurls2 = {\\n \\\"a16z_rss\\\": \\\"https://a16z.com/feed/\\\",\\n \\\"sequoia_rss\\\": \\\"https://www.sequoiacap.com/feed/\\\",\\n \\\"accel_rss\\\": \\\"https://www.accel.com/insights/rss.xml\\\",\\n \\\"bvp_state_cloud_2025\\\": \\\"https://www.bvp.com/insights/state-of-the-cloud-2025\\\",\\n \\\"insight_ai_report\\\": \\\"https://www.insightpartners.com/insights/ai/\\\",\\n \\\"meritech_kbcm_2025\\\": \\\"https://meritechcapital.com/2025-kbcm-saas-survey/\\\",\\n \\\"crunchbase_deals\\\": \\\"https://news.crunchbase.com/venture/\\\",\\n \\\"tc_ai\\\": \\\"https://techcrunch.com/category/artificial-intelligence/\\\",\\n \\\"tc_enterprise\\\": \\\"https://techcrunch.com/category/enterprise/\\\",\\n \\\"reuters_vc\\\": \\\"https://www.reuters.com/technology/\\\",\\n \\\"bloomberg_vc\\\": \\\"https://www.bloomberg.com/technology\\\",\\n \\\"axios_pro_rata\\\": \\\"https://www.axios.com/newsletters/\\\",\\n \\\"svb_state_startup\\\": \\\"https://www.svb.com/trends-insights/reports/state-of-startups\\\",\\n \\\"nvca_2026\\\": \\\"https://nvca.org/press-release/\\\",\\n \\\"pitchbook_nvca\\\": \\\"https://pitchbook.com/news/reports/q1-2025-pitchbook-nvca-venture-monitor\\\",\\n \\\"cbinsights_state_venture_2025\\\": \\\"https://www.cbinsights.com/research/report/state-of-venture-2025/\\\",\\n \\\"cisco_cybersecurity_report\\\": \\\"https://www.cisco.com/c/en/us/products/security/cybersecurity-reports.html\\\",\\n \\\"gartner_ai_spend\\\": \\\"https://www.gartner.com/en/newsroom/artificial-intelligence\\\",\\n \\\"idc_ai_spending\\\": \\\"https://www.idc.com/promo/ai-spending-guide\\\",\\n \\\"mckinsey_ai_report\\\": \\\"https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2025-implementing-ai-innovations\\\"\\n}\\n\\nresults={}\\nfor name,url in urls2.items():\\n print(f\\\"Fetching {name} ...\\\", flush=True)\\n h=fetch(url)\\n results[name] = {\\\"url\\\":url, \\\"len\\\":len(h), \\\"error\\\": h if h.startswith(\\\"ERROR\\\") else None, \\\"prefix\\\":h[:8000]}\\n time.sleep(1.5)\\n\\nwith open(\\\"fetches_raw_2.json\\\",\\\"w\\\",encoding=\\\"utf-8\\\") as f:\\n json.dump(results,f,ensure_ascii=False,indent=2)\\nprint(\\\"Batch 2 done.\\\")\\nPY\\nwc -c fetches_raw_2.json\\n\",\"timeout\":300,\"workdir\":\"/DATA/AppData/research_vc_2026\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"Fetching a16z_rss ...\\nFetching sequoia_rss ...\\nFetching accel_rss ...\\nFetching bvp_state_cloud_2025 ...\\nFetching insight_ai_report ...\\nFetching meritech_kbcm_2025 ...\\nFetching crunchbase_deals ...\\nFetching tc_ai ...\\nFetching tc_enterprise ...\\nFetching reuters_vc ...\\nFetching bloomberg_vc ...\\nFetching axios_pro_rata ...\\nFetching svb_state_startup ...\\nFetching nvca_2026 ...\\nFetching pitchbook_nvca ...\\nFetching cbinsights_state_venture_2025 ...\\nFetching cisco_cybersecurity_report ...\\nFetching gartner_ai_spend ...\\nFetching idc_ai_spending ...\\nFetching mckinsey_ai_report ...\\nBatch 2 done.\\n55167 fetches_raw_2.json\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "functions.terminal:14" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "functions.terminal:15", "call_id": "functions.terminal:15", "response_item_id": "fc_functionsterminal15", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"cd /DATA/AppData/research_vc_2026 \\u0026\\u0026 python3 - \\u003c\\u003c'PY'\\nimport json\\nwith open(\\\"fetches_raw_2.json\\\") as f:\\n data=json.load(f)\\nfor k,v in data.items():\\n print(f\\\"{k:25s} len={v['len']:7d} err={'YES' if v['error'] else 'NO'}\\\")\\nPY\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"a16z_rss len= 43 err=YES\\nsequoia_rss len= 168882 err=NO\\naccel_rss len= 43 err=YES\\nbvp_state_cloud_2025 len= 43 err=YES\\ninsight_ai_report len= 43 err=YES\\nmeritech_kbcm_2025 len= 43 err=YES\\ncrunchbase_deals len= 174365 err=NO\\ntc_ai len= 301480 err=NO\\ntc_enterprise len= 297994 err=NO\\nreuters_vc len= 48 err=YES\\nbloomberg_vc len= 43 err=YES\\naxios_pro_rata len= 43 err=YES\\nsvb_state_startup len= 43 err=YES\\nnvca_2026 len= 43 err=YES\\npitchbook_nvca len= 43 err=YES\\ncbinsights_state_venture_2025 len= 121932 err=NO\\ncisco_cybersecurity_report len= 63231 err=NO\\ngartner_ai_spend len= 43 err=YES\\nidc_ai_spending len= 34 err=YES\\nmckinsey_ai_report len= 49 err=YES\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "functions.terminal:15" }, { "role": "assistant", "content": "", "reasoning": "The many \"43\" error lengths indicate bot protection or 403. I need to use a different strategy: fetch via textise dot iitty, textise dot iitty, or use `textise dot iitty`. Better: use textise dot iitty for some. Or use `https://r.jina.ai/http://URL` to get clean article text. Jina AI summarizer works for many pages and bypasses paywalls/bot checks. Use Jina AI reader for specific articles. Also use textise dot iitty? Let's use jina.ai/http://URL. It fetches arbitrary URLs and returns markdown. This is excellent.\n\nPlan:\n- Use Jina AI reader URLs like `https://r.jina.ai/http://a16z.com/ai/` to get content.\n- Use it for specific VC reports and articles.\n- Use DDG search more carefully; maybe DuckDuckGo blocked after first query. Use `https://html.duckduckgo.com/html/?q=` with maybe rotating user-agent? The first query worked but subsequent returned 0 results. Maybe rate-limit or need parse issue. Actually it may block repeated. Use `lite.duckduckgo.com/lite/?q=` with less bot detection. Let's try.\n- Use `https://www.bing.com/search?q=` maybe blocked.\n- Use `https://r.jina.ai/http://...` for many URLs, not blocked likely.\n\nLet's fetch key sources with Jina: a16z articles list, Sequoia, Benchmark (maybe no blog), Accel, BVP cloud, Insight AI report, Meritech KBCM, Pitchbook NVCA, CB Insights reports, Gartner/IDC AI forecasts, McKinsey State of AI 2025/2026, Crunchbase latest funding rounds, TechCrunch AI and security.\n\nAlso need specific data: recent funding rounds (e.g., Cognition, Poolside, Magic, Harvey, Sierra, etc), VC thesis statements. I can use Jina on Crunchbase news pages, TechCrunch category pages, and maybe specific searches via jina? There is jina search: `https://r.jina.ai/http://s.jina.ai/http://URL?format=text` not. But jina has `https://r.jina.ai/http://s.jina.ai/http://Your+search+query` maybe. Let's use `https://r.jina.ai/http://s.jina.ai/http://VC+trends+2026`? Actually Jina AI search: `https://r.jina.ai/http://s.jina.ai/http://QUERY`. The format: `https://r.jina.ai/http://s.jina.ai/http://What+is+...` maybe. Try.\n\nBut easier: use `https://r.jina.ai/http://news.ycombinator.com` no. For funding rounds, use Crunchbase AI category page via jina. Also maybe use `https://r.jina.ai/http://techcrunch.com/category/artificial-intelligence/`.\n\nWe also have OpenAI API? no. But can use local reasoning.\n\nI need to compile comprehensive research brief in German. I can synthesize from fetched text. Need data accurate. Since current date is 2026-06-20, I need 2026 data but web might not have future. However model knowledge cutoff maybe 2024-early 2025, but web search might give 2025 reports. The user wants \"VC-Trends 2026\". Since it's June 2026, there should be 2026 data. I will use latest available from 2025 and 2026. I should be transparent if exact 2026 data is sparse. I can supplement with known recent rounds from knowledge. But web search likely has 2025 reports; we can use Q1 2026 if available. The task explicitly asks current trends 2026. I will do my best.\n\nLet's proceed with jina fetch for all key pages.", "finish_reason": "tool_calls", "reasoning_content": "The many \"43\" error lengths indicate bot protection or 403. I need to use a different strategy: fetch via textise dot iitty, textise dot iitty, or use `textise dot iitty`. Better: use textise dot iitty for some. Or use `https://r.jina.ai/http://URL` to get clean article text. Jina AI summarizer works for many pages and bypasses paywalls/bot checks. Use Jina AI reader for specific articles. Also use textise dot iitty? Let's use jina.ai/http://URL. It fetches arbitrary URLs and returns markdown. This is excellent.\n\nPlan:\n- Use Jina AI reader URLs like `https://r.jina.ai/http://a16z.com/ai/` to get content.\n- Use it for specific VC reports and articles.\n- Use DDG search more carefully; maybe DuckDuckGo blocked after first query. Use `https://html.duckduckgo.com/html/?q=` with maybe rotating user-agent? The first query worked but subsequent returned 0 results. Maybe rate-limit or need parse issue. Actually it may block repeated. Use `lite.duckduckgo.com/lite/?q=` with less bot detection. Let's try.\n- Use `https://www.bing.com/search?q=` maybe blocked.\n- Use `https://r.jina.ai/http://...` for many URLs, not blocked likely.\n\nLet's fetch key sources with Jina: a16z articles list, Sequoia, Benchmark (maybe no blog), Accel, BVP cloud, Insight AI report, Meritech KBCM, Pitchbook NVCA, CB Insights reports, Gartner/IDC AI forecasts, McKinsey State of AI 2025/2026, Crunchbase latest funding rounds, TechCrunch AI and security.\n\nAlso need specific data: recent funding rounds (e.g., Cognition, Poolside, Magic, Harvey, Sierra, etc), VC thesis statements. I can use Jina on Crunchbase news pages, TechCrunch category pages, and maybe specific searches via jina? There is jina search: `https://r.jina.ai/http://s.jina.ai/http://URL?format=text` not. But jina has `https://r.jina.ai/http://s.jina.ai/http://Your+search+query` maybe. Let's use `https://r.jina.ai/http://s.jina.ai/http://VC+trends+2026`? Actually Jina AI search: `https://r.jina.ai/http://s.jina.ai/http://QUERY`. The format: `https://r.jina.ai/http://s.jina.ai/http://What+is+...` maybe. Try.\n\nBut easier: use `https://r.jina.ai/http://news.ycombinator.com` no. For funding rounds, use Crunchbase AI category page via jina. Also maybe use `https://r.jina.ai/http://techcrunch.com/category/artificial-intelligence/`.\n\nWe also have OpenAI API? no. But can use local reasoning.\n\nI need to compile comprehensive research brief in German. I can synthesize from fetched text. Need data accurate. Since current date is 2026-06-20, I need 2026 data but web might not have future. However model knowledge cutoff maybe 2024-early 2025, but web search might give 2025 reports. The user wants \"VC-Trends 2026\". Since it's June 2026, there should be 2026 data. I will use latest available from 2025 and 2026. I should be transparent if exact 2026 data is sparse. I can supplement with known recent rounds from knowledge. But web search likely has 2025 reports; we can use Q1 2026 if available. The task explicitly asks current trends 2026. I will do my best.\n\nLet's proceed with jina fetch for all key pages.", "tool_calls": [ { "id": "functions.terminal:16", "call_id": "functions.terminal:16", "response_item_id": "fc_functionsterminal16", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"cd /DATA/AppData/research_vc_2026 \\u0026\\u0026 python3 - \\u003c\\u003c'PY'\\nimport json, urllib.request, ssl, time, urllib.parse\\n\\nctx = ssl.create_default_context()\\nctx.check_hostname = False\\nctx.verify_mode = ssl.CERT_NONE\\n\\ndef jina(url, timeout=35):\\n jina_url = \\\"https://r.jina.ai/http://\\\" + urllib.parse.quote(url, safe='/:?=\\u0026')\\n try:\\n req = urllib.request.Request(jina_url, headers={\\\"User-Agent\\\":\\\"Mozilla/5.0\\\"})\\n with urllib.request.urlopen(req, context=ctx, timeout=timeout) as r:\\n return r.read().decode('utf-8', errors='ignore')\\n except Exception as e:\\n return f\\\"ERROR: {type(e).__name__}: {e}\\\"\\n\\ndef jina_search(query, timeout=35):\\n jina_url = \\\"https://r.jina.ai/http://s.jina.ai/http://\\\" + urllib.parse.quote(query)\\n try:\\n req = urllib.request.Request(jina_url, headers={\\\"User-Agent\\\":\\\"Mozilla/5.0\\\"})\\n with urllib.request.urlopen(req, context=ctx, timeout=timeout) as r:\\n return r.read().decode('utf-8', errors='ignore')\\n except Exception as e:\\n return f\\\"ERROR: {type(e).__name__}: {e}\\\"\\n\\nsources = {\\n \\\"a16z_ai_2026\\\": \\\"https://a16z.com/ai/\\\",\\n \\\"a16z_marketplace\\\": \\\"https://a16z.com/marketplace/\\\",\\n \\\"a16z_enterprise_2025\\\": \\\"https://a16z.com/2025/05/08/enterprise-ai/\\\",\\n \\\"a16z_agentic_ai\\\": \\\"https://a16z.com/2025/03/31/ai-agents/\\\",\\n \\\"sequoia_ai\\\": \\\"https://www.sequoiacap.com/article/generative-ai/\\\",\\n \\\"sequoia_2025_ai\\\": \\\"https://www.sequoiacap.com/article/2025-ai-predictions/\\\",\\n \\\"sequoia_arc\\\": \\\"https://www.sequoiacap.com/article/announcing-arc-2026/\\\",\\n \\\"accel_insights\\\": \\\"https://www.accel.com/insights\\\",\\n \\\"bvp_state_cloud_2025\\\": \\\"https://www.bvp.com/insights/state-of-the-cloud-2025\\\",\\n \\\"bvp_bessemer_cloud_index\\\": \\\"https://www.bvp.com/insights/bessemer-cloud-index\\\",\\n \\\"insight_ai_state\\\": \\\"https://www.insightpartners.com/insights/ai/\\\",\\n \\\"meritech_kbcm_2025\\\": \\\"https://meritechcapital.com/2025-kbcm-saas-survey/\\\",\\n \\\"meritech_saas_ai\\\": \\\"https://meritechcapital.com/ai-multiples/\\\",\\n \\\"pitchbook_nvca_q1_2026\\\": \\\"https://pitchbook.com/news/reports/q1-2026-pitchbook-nvca-venture-monitor\\\",\\n \\\"pitchbook_nvca_q4_2025\\\": \\\"https://pitchbook.com/news/reports/q4-2025-pitchbook-nvca-venture-monitor\\\",\\n \\\"cbinsights_state_venture_2025\\\": \\\"https://www.cbinsights.com/research/report/state-of-venture-2025/\\\",\\n \\\"cbinsights_ai_trends_2026\\\": \\\"https://www.cbinsights.com/research/report/state-of-ai-2026/\\\",\\n \\\"crunchbase_ai\\\": \\\"https://news.crunchbase.com/artificial-intelligence/\\\",\\n \\\"crunchbase_venture\\\": \\\"https://news.crunchbase.com/venture/\\\",\\n \\\"tc_ai\\\": \\\"https://techcrunch.com/category/artificial-intelligence/\\\",\\n \\\"tc_security\\\": \\\"https://techcrunch.com/category/security/\\\",\\n \\\"gartner_ai_software\\\": \\\"https://www.gartner.com/en/newsroom/artificial-intelligence\\\",\\n \\\"idc_ai_spending\\\": \\\"https://www.idc.com/promo/ai-spending-guide\\\",\\n \\\"mckinsey_state_ai_2025\\\": \\\"https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2025-implementing-ai-innovations\\\",\\n \\\"cisco_cybersecurity\\\": \\\"https://www.cisco.com/c/en/us/products/security/cybersecurity-reports.html\\\",\\n \\\"cybersecurity_ventures_cost\\\": \\\"https://cybersecurityventures.com/cybercrime-damages-6-trillion-by-2021/\\\",\\n \\\"businessinsider_vc_2026\\\": \\\"https://www.businessinsider.com/venture-capital\\\",\\n \\\"axios_pro_rata\\\": \\\"https://www.axios.com/newsletters/\\\",\\n \\\"nvca_q1_2026\\\": \\\"https://nvca.org/press-release/\\\",\\n \\\"redpoint_ai\\\": \\\"https://www.redpoint.com/blog/\\\",\\n \\\"iconiq_ai\\\": \\\"https://iconiqcapital.com/insights/\\\",\\n \\\"threshold_ai\\\": \\\"https://threshold.vc/blog\\\",\\n \\\"greycroft_ai\\\": \\\"https://greycroft.com/insights/\\\",\\n \\\"battery_ventures_ai\\\": \\\"https://www.battery.com/perspectives/\\\"\\n}\\n\\nresults={}\\nfor name,url in sources.items():\\n print(f\\\"Jina {name} ...\\\", flush=True)\\n txt=jina(url)\\n results[name] = {\\\"url\\\":url, \\\"len\\\":len(txt), \\\"error\\\": txt if txt.startswith(\\\"ERROR\\\") else None, \\\"text\\\":txt[:12000]}\\n time.sleep(1.2)\\n\\n# Jina searches for specific topics\\nsearches = [\\n \\\"VC trends 2026 AI agent funding rounds\\\",\\n \\\"AI agent infrastructure startups funding 2026\\\",\\n \\\"AI security startup funding 2026\\\",\\n \\\"vertical AI agents enterprise funding 2026\\\",\\n \\\"confidential computing AI startup funding\\\",\\n \\\"agent to agent protocol A2A Anthropic Google\\\",\\n \\\"CrowdStrike competitors cybersecurity startups VC 2025 2026\\\",\\n \\\"supply chain security startups VC funding 2026\\\",\\n \\\"prompt injection defense startup funding\\\",\\n \\\"AI agent orchestration SaaS funding rounds 2026\\\",\\n \\\"Cognition AI funding 2025 2026\\\",\\n \\\"Poolside AI funding valuation 2025\\\",\\n \\\"Harvey AI funding 2025 2026\\\",\\n \\\"Sierra AI conversational AI funding 2025\\\",\\n \\\"a16z AI thesis 2025 2026\\\",\\n \\\"Sequoia AI thesis 2025 2026\\\"\\n]\\n\\nsearch_results={}\\nfor q in searches:\\n print(f\\\"Jina search: {q}\\\", flush=True)\\n txt=jina_search(q)\\n search_results[q] = {\\\"len\\\":len(txt), \\\"error\\\": txt if txt.startswith(\\\"ERROR\\\") else None, \\\"text\\\":txt[:10000]}\\n time.sleep(2)\\n\\nwith open(\\\"jina_sources.json\\\",\\\"w\\\",encoding=\\\"utf-8\\\") as f:\\n json.dump(results, f, ensure_ascii=False, indent=2)\\nwith open(\\\"jina_searches.json\\\",\\\"w\\\",encoding=\\\"utf-8\\\") as f:\\n json.dump(search_results, f, ensure_ascii=False, indent=2)\\nprint(\\\"Jina batch done.\\\")\\nPY\\nwc -c jina_sources.json jina_searches.json\\n\",\"timeout\":600,\"workdir\":\"/DATA/AppData/research_vc_2026\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"Jina a16z_ai_2026 ...\\nJina a16z_marketplace ...\\nJina a16z_enterprise_2025 ...\\nJina a16z_agentic_ai ...\\nJina sequoia_ai ...\\nJina sequoia_2025_ai ...\\nJina sequoia_arc ...\\nJina accel_insights ...\\nJina bvp_state_cloud_2025 ...\\nJina bvp_bessemer_cloud_index ...\\nJina insight_ai_state ...\\nJina meritech_kbcm_2025 ...\\nJina meritech_saas_ai ...\\nJina pitchbook_nvca_q1_2026 ...\\nJina pitchbook_nvca_q4_2025 ...\\nJina cbinsights_state_venture_2025 ...\\nJina cbinsights_ai_trends_2026 ...\\nJina crunchbase_ai ...\\nJina crunchbase_venture ...\\nJina tc_ai ...\\nJina tc_security ...\\nJina gartner_ai_software ...\\nJina idc_ai_spending ...\\nJina mckinsey_state_ai_2025 ...\\nJina cisco_cybersecurity ...\\nJina cybersecurity_ventures_cost ...\\nJina businessinsider_vc_2026 ...\\nJina axios_pro_rata ...\\nJina nvca_q1_2026 ...\\nJina redpoint_ai ...\\nJina iconiq_ai ...\\nJina threshold_ai ...\\nJina greycroft_ai ...\\nJina battery_ventures_ai ...\\nJina search: VC trends 2026 AI agent funding rounds\\nJina search: AI agent infrastructure startups funding 2026\\nJina search: AI security startup funding 2026\\nJina search: vertical AI agents enterprise funding 2026\\nJina search: confidential computing AI startup funding\\nJina search: agent to agent protocol A2A Anthropic Google\\nJina search: CrowdStrike competitors cybersecurity startups VC 2025 2026\\nJina search: supply chain security startups VC funding 2026\\nJina search: prompt injection defense startup funding\\nJina search: AI agent orchestration SaaS funding rounds 2026\\nJina search: Cognition AI funding 2025 2026\\nJina search: Poolside AI funding valuation 2025\\nJina search: Harvey AI funding 2025 2026\\nJina search: Sierra AI conversational AI funding 2025\\nJina search: a16z AI thesis 2025 2026\\nJina search: Sequoia AI thesis 2025 2026\\nJina batch done.\\n219532 jina_sources.json\\n 10300 jina_searches.json\\n229832 total\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "functions.terminal:16" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "functions.terminal:17", "call_id": "functions.terminal:17", "response_item_id": "fc_functionsterminal17", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"cd /DATA/AppData/research_vc_2026 \\u0026\\u0026 python3 - \\u003c\\u003c'PY'\\nimport json\\nwith open(\\\"jina_sources.json\\\") as f:\\n data=json.load(f)\\nfor k,v in data.items():\\n print(f\\\"{k:30s} len={v['len']:7d} err={'YES' if v['error'] else 'NO'}\\\")\\nPY\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"a16z_ai_2026 len= 35528 err=NO\\na16z_marketplace len= 3137 err=NO\\na16z_enterprise_2025 len= 3163 err=NO\\na16z_agentic_ai len= 3155 err=NO\\nsequoia_ai len= 1654 err=NO\\nsequoia_2025_ai len= 1673 err=NO\\nsequoia_arc len= 1671 err=NO\\naccel_insights len= 22947 err=NO\\nbvp_state_cloud_2025 len= 5466 err=NO\\nbvp_bessemer_cloud_index len= 5463 err=NO\\ninsight_ai_state len= 8569 err=NO\\nmeritech_kbcm_2025 len= 229 err=NO\\nmeritech_saas_ai len= 220 err=NO\\npitchbook_nvca_q1_2026 len= 335 err=NO\\npitchbook_nvca_q4_2025 len= 499 err=NO\\ncbinsights_state_venture_2025 len= 14170 err=NO\\ncbinsights_ai_trends_2026 len= 14150 err=NO\\ncrunchbase_ai len= 20365 err=NO\\ncrunchbase_venture len= 32593 err=NO\\ntc_ai len= 23050 err=NO\\ntc_security len= 25208 err=NO\\ngartner_ai_software len= 342 err=NO\\nidc_ai_spending len= 10967 err=NO\\nmckinsey_state_ai_2025 len= 492 err=NO\\ncisco_cybersecurity len= 68059 err=NO\\ncybersecurity_ventures_cost len= 18436 err=NO\\nbusinessinsider_vc_2026 len= 18240 err=NO\\naxios_pro_rata len= 460 err=NO\\nnvca_q1_2026 len= 12142 err=NO\\nredpoint_ai len= 1390 err=NO\\niconiq_ai len= 420 err=NO\\nthreshold_ai len= 3269 err=NO\\ngreycroft_ai len= 1762 err=NO\\nbattery_ventures_ai len= 12299 err=NO\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "functions.terminal:17" }, { "role": "assistant", "content": "", "reasoning": "Viele Jina-Extrakte sind sehr kurz (ca. 220–5000 Zeichen), d.h. Jina hat nicht den vollständigen Artikelinhalt geliefert. Aber einige wichtige haben längere Inhalte: a16z_ai_2026 (35k), cbinsights (14k), crunchbase venture (32k), tc_security (25k), tc_ai (23k), cisco_cybersecurity (68k), businessinsider (18k), battery (12k), idc (11k), nvca (12k), accel (23k). Das ist genug, um einen soliden Research-Brief zu schreiben.\n\nIch sollte noch mehr spezifische Inhalte zu KI-Agenten-Firmen, aktuellen Runden, Marktgrößen und VC-Thesen sammeln. Ich nutze Jina-Suche und einzelne Artikel-URLs direkt. Ich konzentriere mich auf:\n- Agentic AI / AI Agent Startups: Cognition, Poolside, Anthropic Computer Use, Sierra, Adept (acquired by Amazon), Character, Inflection, etc.\n- AI Security / Model Security / Prompt Injection: HiddenLayer, Robust Intelligence, Lakera, Protect AI, Arthur, etc.\n- Cybersecurity: Wiz, CrowdStrike, Orca, Snyk, Semgrep, Vanta, Drata\n- Confidential Computing: Anjuna, Fortanix, etc.\n- Market sizes: Gartner/IDC/McKinsey numbers\n- VC firms theses\n\nIch will parallel viele Jina-Aufrufe machen.", "finish_reason": "tool_calls", "reasoning_content": "Viele Jina-Extrakte sind sehr kurz (ca. 220–5000 Zeichen), d.h. Jina hat nicht den vollständigen Artikelinhalt geliefert. Aber einige wichtige haben längere Inhalte: a16z_ai_2026 (35k), cbinsights (14k), crunchbase venture (32k), tc_security (25k), tc_ai (23k), cisco_cybersecurity (68k), businessinsider (18k), battery (12k), idc (11k), nvca (12k), accel (23k). Das ist genug, um einen soliden Research-Brief zu schreiben.\n\nIch sollte noch mehr spezifische Inhalte zu KI-Agenten-Firmen, aktuellen Runden, Marktgrößen und VC-Thesen sammeln. Ich nutze Jina-Suche und einzelne Artikel-URLs direkt. Ich konzentriere mich auf:\n- Agentic AI / AI Agent Startups: Cognition, Poolside, Anthropic Computer Use, Sierra, Adept (acquired by Amazon), Character, Inflection, etc.\n- AI Security / Model Security / Prompt Injection: HiddenLayer, Robust Intelligence, Lakera, Protect AI, Arthur, etc.\n- Cybersecurity: Wiz, CrowdStrike, Orca, Snyk, Semgrep, Vanta, Drata\n- Confidential Computing: Anjuna, Fortanix, etc.\n- Market sizes: Gartner/IDC/McKinsey numbers\n- VC firms theses\n\nIch will parallel viele Jina-Aufrufe machen.", "tool_calls": [ { "id": "functions.terminal:18", "call_id": "functions.terminal:18", "response_item_id": "fc_functionsterminal18", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"cd /DATA/AppData/research_vc_2026 \\u0026\\u0026 python3 - \\u003c\\u003c'PY'\\nimport json, urllib.request, ssl, time, urllib.parse\\n\\nctx = ssl.create_default_context()\\nctx.check_hostname = False\\nctx.verify_mode = ssl.CERT_NONE\\n\\ndef jina(url, timeout=35):\\n jina_url = \\\"https://r.jina.ai/http://\\\" + urllib.parse.quote(url, safe='/:?=\\u0026')\\n try:\\n req = urllib.request.Request(jina_url, headers={\\\"User-Agent\\\":\\\"Mozilla/5.0\\\"})\\n with urllib.request.urlopen(req, context=ctx, timeout=timeout) as r:\\n return r.read().decode('utf-8', errors='ignore')\\n except Exception as e:\\n return f\\\"ERROR: {type(e).__name__}: {e}\\\"\\n\\n# Direct URLs of specific articles / data sources\\nsources2 = {\\n \\\"a16z_2025_market_maps\\\": \\\"https://a16z.com/2025/06/11/market-map-ai-application-layer/\\\",\\n \\\"a16z_ai_infrastructure\\\": \\\"https://a16z.com/2025/05/30/ai-infrastructure/\\\",\\n \\\"a16z_agentic_platforms\\\": \\\"https://a16z.com/2025/04/24/agentic-ai-platforms/\\\",\\n \\\"a16z_voice_agents\\\": \\\"https://a16z.com/2025/05/16/voice-agents/\\\",\\n \\\"a16z_cybersecurity_ai\\\": \\\"https://a16z.com/2025/03/18/ai-cybersecurity/\\\",\\n \\\"sequoia_2025_cloud\\\": \\\"https://www.sequoiacap.com/article/2025-cloud/\\\",\\n \\\"sequoia_2025_ai_apps\\\": \\\"https://www.sequoiacap.com/article/2025-ai-applications/\\\",\\n \\\"sequoia_2025_security\\\": \\\"https://www.sequoiacap.com/article/2025-security/\\\",\\n \\\"sequoia_2025_b2b\\\": \\\"https://www.sequoiacap.com/article/2025-b2b/\\\",\\n \\\"bvp_state_cloud_2025_pdf\\\": \\\"https://www.bvp.com/insights/state-of-the-cloud-2025\\\",\\n \\\"meritech_2025_saas_survey\\\": \\\"https://meritechcapital.com/2025-kbcm-saas-survey\\\",\\n \\\"insight_2025_ai_report\\\": \\\"https://www.insightpartners.com/insights/ai/index.html\\\",\\n \\\"battery_ai_2025\\\": \\\"https://www.battery.com/perspectives/ai-2025/\\\",\\n \\\"redpoint_2025_ai\\\": \\\"https://www.redpoint.com/blog/2025-the-year-of-ai-agents/\\\",\\n \\\"iconiq_ai_2025\\\": \\\"https://iconiqcapital.com/insights/2025-ai-outlook/\\\",\\n \\\"threshold_2025_ai\\\": \\\"https://threshold.vc/blog/2025-ai-agent/\\\",\\n \\\"tc_cognition_funding\\\": \\\"https://techcrunch.com/2025/06/19/cognition-ai/\\\",\\n \\\"tc_poolside_funding\\\": \\\"https://techcrunch.com/2025/05/08/poolside/\\\",\\n \\\"tc_harvey_funding\\\": \\\"https://techcrunch.com/2025/02/04/harvey-ai/\\\",\\n \\\"tc_sierra_funding\\\": \\\"https://techcrunch.com/2025/01/23/sierra-conversational-ai/\\\",\\n \\\"crunchbase_anthropic_funding\\\": \\\"https://news.crunchbase.com/anthropic/\\\",\\n \\\"crunchbase_cognition\\\": \\\"https://news.crunchbase.com/cognition-ai/\\\",\\n \\\"crunchbase_poolside\\\": \\\"https://news.crunchbase.com/poolside/\\\",\\n \\\"businessinsider_vc_2025_year\\\": \\\"https://www.businessinsider.com/venture-capital-2025-year-review\\\",\\n \\\"cbinsights_unicorn_list\\\": \\\"https://www.cbinsights.com/research/artificial-intelligence-unicorns/\\\",\\n \\\"cbinsights_ai_100\\\": \\\"https://www.cbinsights.com/research/ai-100/\\\",\\n \\\"gartner_ai_software_2026\\\": \\\"https://www.gartner.com/en/newsroom/press-releases/2025-03-26-gartner-forecasts-worldwide-ai-software-spending-to-grow-35-percent-in-2025\\\",\\n \\\"gartner_security_2026\\\": \\\"https://www.gartner.com/en/newsroom/press-releases/2025-03-26-gartner-forecasts-worldwide-security-software-spending-to-grow-12-percent-in-2025\\\",\\n \\\"mckinsey_state_ai_2025\\\": \\\"https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2025-generative-ais-breakout-year\\\",\\n \\\"idc_ai_spending_2026\\\": \\\"https://www.idc.com/getdoc.jsp?containerId=prUS53447423\\\",\\n \\\"wef_cybercrime_2026\\\": \\\"https://www.weforum.org/stories/2025/01/cybercrime-costs-global-economy-trillion/\\\",\\n \\\"hiddenlayer_funding\\\": \\\"https://techcrunch.com/2023/12/14/hiddenlayer/\\\",\\n \\\"robust_intelligence_funding\\\": \\\"https://techcrunch.com/2024/04/25/robust-intelligence/\\\",\\n \\\"protect_ai_funding\\\": \\\"https://techcrunch.com/2024/07/18/protect-ai/\\\",\\n \\\"lakera_funding\\\": \\\"https://techcrunch.com/2024/06/25/lakera/\\\",\\n \\\"snyk_funding\\\": \\\"https://techcrunch.com/2025/02/25/snyk/\\\",\\n \\\"wiz_funding\\\": \\\"https://techcrunch.com/2025/04/08/wiz/\\\",\\n \\\"wiz_google_acquisition\\\": \\\"https://techcrunch.com/2025/03/18/wiz-google-acquisition/\\\",\\n \\\"semgrep_funding\\\": \\\"https://techcrunch.com/2024/12/03/semgrep/\\\",\\n \\\"orca_funding\\\": \\\"https://techcrunch.com/2025/02/18/orca-security/\\\",\\n \\\"vanta_funding\\\": \\\"https://techcrunch.com/2025/01/14/vanta/\\\",\\n \\\"drata_funding\\\": \\\"https://techcrunch.com/2024/12/17/drata/\\\",\\n \\\"cato_networks_funding\\\": \\\"https://techcrunch.com/2025/02/25/cato-networks/\\\",\\n \\\"cyera_funding\\\": \\\"https://techcrunch.com/2025/04/09/cyera/\\\",\\n \\\"databricks_funding\\\": \\\"https://techcrunch.com/2025/01/29/databricks/\\\",\\n \\\"openai_funding\\\": \\\"https://techcrunch.com/2025/04/14/openai-funding/\\\",\\n \\\"xai_funding\\\": \\\"https://techcrunch.com/2025/03/31/xai-funding/\\\"\\n}\\n\\nresults={}\\nfor name,url in sources2.items():\\n print(f\\\"Jina {name} ...\\\", flush=True)\\n txt=jina(url)\\n results[name] = {\\\"url\\\":url, \\\"len\\\":len(txt), \\\"error\\\": txt if txt.startswith(\\\"ERROR\\\") else None, \\\"text\\\":txt[:12000]}\\n time.sleep(1.0)\\n\\nwith open(\\\"jina_sources_2.json\\\",\\\"w\\\",encoding=\\\"utf-8\\\") as f:\\n json.dump(results, f, ensure_ascii=False, indent=2)\\nprint(\\\"Jina sources 2 done.\\\")\\nPY\\nwc -c jina_sources_2.json\\n\",\"timeout\":600,\"workdir\":\"/DATA/AppData/research_vc_2026\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"Jina a16z_2025_market_maps ...\\nJina a16z_ai_infrastructure ...\\nJina a16z_agentic_platforms ...\\nJina a16z_voice_agents ...\\nJina a16z_cybersecurity_ai ...\\nJina sequoia_2025_cloud ...\\nJina sequoia_2025_ai_apps ...\\nJina sequoia_2025_security ...\\nJina sequoia_2025_b2b ...\\nJina bvp_state_cloud_2025_pdf ...\\nJina meritech_2025_saas_survey ...\\nJina insight_2025_ai_report ...\\nJina battery_ai_2025 ...\\nJina redpoint_2025_ai ...\\nJina iconiq_ai_2025 ...\\nJina threshold_2025_ai ...\\nJina tc_cognition_funding ...\\n\\n[Command interrupted]\", \"exit_code\": 130, \"error\": null}", "tool_call_id": "functions.terminal:18" } ] }