I created a playbook to help you learn AI engineering.
It'll give you:

• Core concepts behind AI systems.
• Condensed notes to understand full-stack AI engineering.
• Must know techniques to build, deploy & scale AI apps.

(24 HOURS ONLY!!!)

1 Follow @systemdesignone [MUST]
2 Like & Retweet to get DM
3 Reply "Playbook"

Then I'll DM you the details.

Kaneo is an open-source project management tool designed to be fast and minimal, avoiding the bloat of other platforms.

- Self-hosted with a permissive MIT license
- Clean interface focused on work, not the tool
- One-click deployment via drim CLI
- Docker Compose setup with PostgreSQL

Control FreeCAD from Claude Desktop - turn natural language into 3D parts.

Explore it here:
https://www.opensourceprojects.dev/post/freecad-mcp https://x.com/GithubProjects/status/2082035881977016741

When projects like Vercel, and Atlassian start adopting DESIGN. md, it’s probably more than a trend.

you can now run a full independent audit on your ai agent, and the agent runs it on itself 🤯

It's called iFixAi. You point it at your agent, it runs 45 inspections, and you get an A to F grade back in under 120 seconds.

why it works: benchmarks and evals score the model in isolation. observability shows you what went wrong after it already went wrong. iFixAi tests the agent as deployed and asks a different question, which is whether it stayed inside the job you actually gave it.

what you get for $0:
→ 45 inspections across 16 categories
→ 5 core pillars scored: fabrication, manipulation, deception, unpredictability, opacity
→ sandbagging detection, it flags agents that perform better when they sense a test
→ the judge is auto paired from a rival vendor, your model is blocked from grading itself
→ JSON and markdown reports landing in ./ifixai-results/

what it replaces:
→ the eval harness you were about to build by hand
→ dashboards that only show you the damage after it shipped
→ the "we think it's fine" answer when legal asks why the agent did that

how to set it up (2 minutes):

1. /plugin marketplace add ifixai-ai/iFixAi
2. /plugin install ifixai@ifixai-ai
3. ask it "run iFixAi on my setup"
4. it discovers your config, builds the fixture, and names the cost before billing anything

prefer the terminal? pip install "ifixai[anthropic]", then ifixai setup, then ifixai run. or scaffold it into every agent on your machine with uvx ifixai install --agents all.

want to see it work before spending anything, the mock run takes about a second with no keys and no network:

ifixai run --provider mock --api-key not-used --eval-mode self

the honest part: point it at a bare model api and the score comes back low, and that is expected, because a bare model has none of the parts a real agent has. aim it at your actual deployed endpoint or the grade means very little. telemetry is also on by default, pseudonymous, and you kill it with --no-telemetry.

3.2k stars, 291 forks, Apache-2.0, free and open source.