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Function Calling
📞 Function Calling
Specific
Tool Use, API Integration, Structured Outputs, Agent Actions
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224
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ms
Prompt Injection in RAG
Agentic
Systems
✍️
Prompt Engineering
ulad.net
·
2d
2 days ago
·
Hacker News
Actions for Prompt Injection in RAG Agentic Systems
Adrarsh Divakaran: Building AI
Agents
in Python
🤖
Agent
Content type:
Blog
blog.adarshd.dev
·
6d
6 days ago
Actions for Adrarsh Divakaran: Building AI Agents in Python
How to Defend Against Prompt Injection in Production
✍️
Prompt Engineering
Content type:
Reference
leanpub.com
·
2d
2 days ago
·
DEV
Actions for How to Defend Against Prompt Injection in Production
Tejas-TA/predikit: The missing bridge between your ML
models
and your AI
agents
.
🤖
AI
Content type:
Code
github.com
·
9h
9 hours ago
·
Hacker News
Actions for Tejas-TA/predikit: The missing bridge between your ML models and your AI agents.
Show HN: Run Llama.cpp In-Process from Java with Project Panama FFM
🦙
Llama
deemwar-products.github.io
·
5d
5 days ago
·
Hacker News
Actions for Show HN: Run Llama.cpp In-Process from Java with Project Panama FFM
Location: Lubbock, TX, USA Remote: Yes (Remote-friendly, US-based) Technologies:...
🧠
OpenAI
Content type:
Discussion
news.ycombinator.com
·
12h
12 hours ago
·
Hacker News
Actions for Location: Lubbock, TX, USA Remote: Yes (Remote-friendly, US-based) Technologies:...
Apple's Foundation
Models
can now use third-party LLMs (Claude, Gemini) [video]
🤖
LLM
developer.apple.com
·
3d
3 days ago
·
Hacker News
Actions for Apple's Foundation Models can now use third-party LLMs (Claude, Gemini) [video]
How to Build an AI
Agent
: Step-by-Step with Python
🤖
Agent
Content type:
Blog
udacity.com
·
5d
5 days ago
Actions for How to Build an AI Agent: Step-by-Step with Python
How I Built a Hotel AI Platform in Go (And Every Honest Technical Debt We're Carrying)
🤖
Agent
Content type:
Blog
medium.com
·
6d
6 days ago
·
DEV
Actions for How I Built a Hotel AI Platform in Go (And Every Honest Technical Debt We're Carrying)
Pushing the Limits of
LLM
Tool
Calling
via Experiential Knowledge Integration and Activation
🤖
LLM
Content type:
Academic
arxiv.org
·
1d
1 day ago
Actions for Pushing the Limits of LLM Tool Calling via Experiential Knowledge Integration and Activation
feat(plugins): allow installed trusted policy contracts · openclaw/openclaw@de4b8d8
🔓
Open Source
Content type:
Code
github.com
·
21h
21 hours ago
Actions for feat(plugins): allow installed trusted policy contracts · openclaw/openclaw@de4b8d8
New comment by YadavPankaj79 in "Ask HN: Who wants to be hired? (June 2026)"
✨
Gemini
drive.google.com
·
5d
5 days ago
·
Hacker News
Actions for New comment by YadavPankaj79 in "Ask HN: Who wants to be hired? (June 2026)"
T1-Bench: Benchmarking Multi-Scenario
Agents
in Real-World Domains
🤖
LLM
Content type:
Academic
arxiv.org
·
1d
1 day ago
Actions for T1-Bench: Benchmarking Multi-Scenario Agents in Real-World Domains
New comment by yorktanaka2024 in "Ask HN: Who wants to be hired? (June 2026)"
🔍
RAG
Content type:
Discussion
news.ycombinator.com
·
1d
1 day ago
·
Hacker News
Actions for New comment by yorktanaka2024 in "Ask HN: Who wants to be hired? (June 2026)"
keyuchen21/agentic-engineering-handbook
: The definitive
OpenAI
, Claude, MCP, Harness, Evals, and Production Agent Systems learning roadmap.
🤖
Agent
Content type:
Code
github.com
·
1d
1 day ago
·
Hacker News
Actions for keyuchen21/agentic-engineering-handbook: The definitive OpenAI, Claude, MCP, Harness, Evals, and Production Agent Systems learning roadmap.
New comment by pknerd in "Ask HN: Who wants to be hired? (June 2026)"
⛓️
LangChain
Content type:
Discussion
news.ycombinator.com
·
4d
4 days ago
·
Hacker News
Actions for New comment by pknerd in "Ask HN: Who wants to be hired? (June 2026)"
ashp15205/guardian-runtime: A zero-latency, local-first runtime firewall for LLMs. Intercept every prompt and response locally to stop data leaks and runaway token costs.
🤖
Agent
Content type:
Code
github.com
·
1d
1 day ago
·
Hacker News
Actions for ashp15205/guardian-runtime: A zero-latency, local-first runtime firewall for LLMs. Intercept every prompt and response locally to stop data leaks and runaway token costs.
Skill-3D: Evolving Scene-Aware Skills for
Agentic
3D Spatial Reasoning
✨
Gemini
Content type:
Academic
arxiv.org
·
3d
3 days ago
Actions for Skill-3D: Evolving Scene-Aware Skills for Agentic 3D Spatial Reasoning
New comment by TemuulenBM in "Ask HN: Who wants to be hired? (June 2026)"
🤖
LLM
Content type:
Discussion
news.ycombinator.com
·
3d
3 days ago
·
Hacker News
Actions for New comment by TemuulenBM in "Ask HN: Who wants to be hired? (June 2026)"
cruxial-ai/cruxial: The reliability layer for
LLM
tool
calls
. Intercepts every call, validates arguments against your schema, auto-repairs hallucinated args.
🧠
OpenAI
Content type:
Code
github.com
·
2d
2 days ago
·
r/PromptEngineering
Actions for cruxial-ai/cruxial: The reliability layer for LLM tool calls. Intercepts every call, validates arguments against your schema, auto-repairs hallucinated args.
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