# AI agent Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/ai-agent
> Markdown URL: https://aitinkerers.org/technologies/ai-agent.md
> Technology record last updated: 2026-02-24T00:23:07Z
> Generated: 2026-09-20T15:43:47Z

AI agents are autonomous software systems (driven by LLMs) that plan, reason, and execute complex, multi-step tasks without continuous human oversight.

This technology represents the next major leap in AI: autonomous execution. Unlike basic chatbots, agents use a Perceive-Decide-Act-Learn cycle to achieve high-level goals. They integrate tools (APIs, databases, web search) to perform complex workflows like IT automation, software design, and end-to-end lead generation. Platforms like AutoGPT and LangChain enable this development, moving AI from an assistant role to a proactive, digital worker. The market reflects this impact: it hit $7.6 billion in 2025 and is projected for 49.6% annual growth through 2033.

- Official technology site: https://www.ibm.com/topics/ai-agent
- Public AI Tinkerers demos and talks: 8
- Result page: 1 of 1

## Recent Public Talks and Demos

### [AI-Assisted WordPress Vulnerability Hunting: From Plugin Code to Verified Findings](https://dallas-fort-worth.aitinkerers.org/talks/rsvp_ryp2dvTokTM)

I built a repeatable AI-assisted workflow for finding and validating vulnerabilities in WordPress plugins. In the demo, I’ll show the process end-to-end: selecting a plugin, launching a controlled test environment with a custom harness, then using Codex and a tailored AGENTS.md to scan the source, trace risky execution paths, validate the finding with a proof of concept, and generate a disclosure-ready report.

- Event context: AI Tinkerers Dallas-Fort Worth: June Meetup with Rasa — 2026-06-04 — Dallas Fort Worth
- Public talk page: https://dallas-fort-worth.aitinkerers.org/talks/rsvp_ryp2dvTokTM

### [Building a Persistent Memory & Stateful Second Brain AI Agent](https://dhaka.aitinkerers.org/talks/rsvp_kSMaLnvvGGg)

Demonstrating context engineering in practice through Slatekore - an open-source starter kit that gives Gemini CLI persistent memory using Obsidian as the storage layer. 1. State Management Without Infrastructure How to use the file system as persistent state - your Obsidian vault becomes both the agent's memory and its knowledge base. No databases, no vector stores, no MLOps. 2. Context Engineering for Agent Behavior Crafting system prompts (GEMINI.md) and workflow files that define agent capabilities, constraints, and multi-step reasoning patterns. The prompt is the agent's configuration. 3. Tool Use Through Natural Interfaces Connecting the agent to real actions: creating files, managing tasks, building knowledge graphs - all through natural language commands backed by structured templates. Watch a stateful agent capture research, recall context from previous sessions, update its knowledge graph, and execute project workflows - without any model training or fine-tuning.

- Event context: AI Tinkerers Dhaka 2nd Meetup: Dhaka Builds with AI! — 2026-02-07 — Dhaka
- Public talk page: https://dhaka.aitinkerers.org/talks/rsvp_kSMaLnvvGGg

### [AI All the Way Down: Building a Production Fuel Pricing System with 5 AI Agents](https://st-louis.aitinkerers.org/talks/rsvp_uWD0V_b2O1k)

I am a former long time CIO at High Tech manufacturer Laird Technologies (15 years), and then DuPont (https://www.linkedin.com/in/mattmizell/). I have recently joined a small local company named Better Day Energy to build the entire technology stack for last mile petroleum delivery. I am using AI to develop, and also run a lot of the backed. As an example: We use Claude Code to build AI agents in n8n and python that parse emails and monitor AI parsing failures. It's AI turtles all the way down—and it actually works in production.

- Event context: AI Tinkerers – St. Louis Meetup: February 4, 2026 — 2026-02-04 — St. Louis
- Public talk page: https://st-louis.aitinkerers.org/talks/rsvp_uWD0V_b2O1k

### [Make any LLM improve itself automatically](https://bogota.aitinkerers.org/talks/rsvp_jY2faxRiAQw)

In this demo, we’ll showcase Handit, a tool to make any AI agent or LLM improve itself automatically. You’ll see how Handit enables models to monitor their performance, identify weaknesses, and adapt autonomously using real-time feedback. We’ll walk through the process of setting up a self-improving LLM, demonstrating how the platform analyzes outputs, detects areas for optimization, and evolves the model to handle new challenges. This isn’t just about monitoring—it’s about building smarter, dynamic AI systems that grow and improve on their own.

- Event context: AI Tinkerers Bogotá - January Meetup — 2025-01-30 — Bogotá
- Public talk page: https://bogota.aitinkerers.org/talks/rsvp_jY2faxRiAQw

### [Heal.dev demo](https://paris.aitinkerers.org/talks/rsvp_9fLF913HZS0)

I built Heal.dev https://www.heal.dev/, an AI agent that takes care of website UI testing automatically

- Event context: AI Tinkerers - Paris Meetup on October 15th — 2024-10-15 — Paris
- Public talk page: https://paris.aitinkerers.org/talks/rsvp_9fLF913HZS0

### [What we learned building an AI Agent for 11,000 users](https://nyc.aitinkerers.org/talks/rsvp_C2dcvWb22Dc)

For 9 months, we built and released an AI Agent used by 11,000 people across 40 companies. This is a talk about how we build it and what we've learned from it breaking over and over again.

- Event context: AI Tinkerers August Meetup — 2024-08-28 — New York City
- Public talk page: https://nyc.aitinkerers.org/talks/rsvp_C2dcvWb22Dc

### [Milton - AI agent for economic data analysis](https://singapore.aitinkerers.org/talks/rsvp_Z0VAQIJHtw0)

Every single step of writing an economic data report can be automated using LLMs. I show a demo that does 1. Searching for the right datasets, self-critique and reflection 2. Automatic code-writing with self-debugging 3. Graphing according to the user needs 4. Packaging all of these into a report that rivals the quality of research made on Wall St

- Event context: AI Tinkerers Singapore: Inaugural Meetup - August 2nd, 2024 — 2024-08-02 — Singapore
- Public talk page: https://singapore.aitinkerers.org/talks/rsvp_Z0VAQIJHtw0

### [KushoAI - AI Agent for API Testing](https://bengaluru.aitinkerers.org/talks/rsvp_9mPolBV8Ja8)

Kusho helps you reclaim engineering team bandwidth and ship fast without worrying about unnoticed bugs. Kusho's fine-tuned models are trained to understand API context, write and execute comprehensive tests, and provide analyzed results for debugging, all in sync with your CI/CD process. With Kusho, you get an auto-updating testing set up across hundreds of APIs in hours.

- Event context: AI Tinkerers - Bangalore Inaugural - RSVP REQUIRED — 2024-06-02 — Bengaluru
- Public talk page: https://bengaluru.aitinkerers.org/talks/rsvp_9mPolBV8Ja8

## Related Technologies

- [RAG](https://aitinkerers.org/technologies/rag) ([Markdown](https://aitinkerers.org/technologies/rag.md)) — 147 public demos
- [AGENTS](https://aitinkerers.org/technologies/agents) ([Markdown](https://aitinkerers.org/technologies/agents.md)) — 20 public demos
- [Anthropic](https://aitinkerers.org/technologies/anthropic) ([Markdown](https://aitinkerers.org/technologies/anthropic.md)) — 36 public demos
- [APIs](https://aitinkerers.org/technologies/apis) ([Markdown](https://aitinkerers.org/technologies/apis.md)) — 19 public demos
- [API Testing](https://aitinkerers.org/technologies/api-testing) ([Markdown](https://aitinkerers.org/technologies/api-testing.md)) — 3 public demos
- [AppDynamics](https://aitinkerers.org/technologies/appdynamics) ([Markdown](https://aitinkerers.org/technologies/appdynamics.md)) — 1 public demo
- [ARM](https://aitinkerers.org/technologies/arm) ([Markdown](https://aitinkerers.org/technologies/arm.md)) — 1 public demo
- [AVX2](https://aitinkerers.org/technologies/avx2) ([Markdown](https://aitinkerers.org/technologies/avx2.md)) — 1 public demo
- [BERT](https://aitinkerers.org/technologies/bert) ([Markdown](https://aitinkerers.org/technologies/bert.md)) — 179 public demos
- [BLOOM](https://aitinkerers.org/technologies/bloom) ([Markdown](https://aitinkerers.org/technologies/bloom.md)) — 115 public demos
- [ChromeDriver](https://aitinkerers.org/technologies/chromedriver) ([Markdown](https://aitinkerers.org/technologies/chromedriver.md)) — 1 public demo
- [CI/CD](https://aitinkerers.org/technologies/ci-cd) ([Markdown](https://aitinkerers.org/technologies/ci-cd.md)) — 7 public demos
- [Claude-3](https://aitinkerers.org/technologies/claude-3) ([Markdown](https://aitinkerers.org/technologies/claude-3.md)) — 110 public demos
- [Claude Code](https://aitinkerers.org/technologies/claude-code) ([Markdown](https://aitinkerers.org/technologies/claude-code.md)) — 214 public demos
- [Code](https://aitinkerers.org/technologies/code) ([Markdown](https://aitinkerers.org/technologies/code.md)) — 9 public demos
- [Codex](https://aitinkerers.org/technologies/codex) ([Markdown](https://aitinkerers.org/technologies/codex.md)) — 44 public demos
- [Cypress](https://aitinkerers.org/technologies/cypress) ([Markdown](https://aitinkerers.org/technologies/cypress.md)) — 2 public demos
- [Datadog](https://aitinkerers.org/technologies/datadog) ([Markdown](https://aitinkerers.org/technologies/datadog.md)) — 1 public demo