umesh

[Paradis @ParadisLabs]

Recommended reading for the weekend:

1. @alexandr_wang — Why I'm Building Muse
2. @gregisenberg — AI-native services: a $100B opportunity
3. @FranklnTempletn — Macro Views: Growth Holds, Pressure Builds
4. @Google — Behind Project Suncatcher, our moonshot to put AI in space
5. @EpochAIResearch — The plunging price of thought
6. @AnthropicAI — Measurements for
understanding the pace of AI development inside frontier labs

Hope everyone has a great weekend!

[Gergely Orosz @GergelyOrosz]

That DHH saying out loud that the age of writing code by hand is over for the industry, and causing such a huge uproar is a bit interesting, given this was clear enough since ~January for most of us using the models + paying attention.

Removed paywall: https://t.co/sSfyCm8jk8

[Matt Pocock @mattpocockuk]

Someone just DM'd me saying they:

- Took my courses
- Became the "AI person" at work
- Got asked to run internal trainings
- Feel guilty (like they're taking work away from me)

Don't feel guilty! This is my DREAM end state for my students.

Knowledge is still valuable. Becoming the AI guy/gal at your company can totally change your career.

If you're in this position too, let me know how I can help you run your trainings - materials/advice etc.

[Neo Kim @systemdesignone]

AI Engineering — Ultimate Roadmap (SAVE THIS)!

├── 01. LLM Fundamentals
│ ├── Transformers & Attention
│ ├── Inference & Decoding
│ ├── Tokenization
│ └── Context Window & Limits
│
├── 02. Prompting & Context
│ ├── Prompting & In-Context Learning
│ ├── Context Engineering
│ ├── Structured Outputs & Schemas
│ └── Constrained Decoding
│
├── 03. Representations
│ ├── Embeddings
│ ├── Similarity Search
│ ├── Vector Databases
│ └── Hybrid Retrieval
│
├── 04. RAG
│ ├── Chunking
│ ├── Hybrid Search
│ ├── Reranking
│ ├── Query Rewriting
│ └── GraphRAG
│
├── 05. Tools & Agents
│ ├── Tool / Function Calling
│ ├── Agentic Workflows
│ ├── Agent Memory & State
│ ├── MCP
│ ├── A2A / Interoperability
│ └── Human-in-the-Loop
│
├── 06. Evaluation
│ ├── Evals
│ ├── Test Datasets
│ ├── Online Metrics
│ └── Tracing & Debugging
│
├── 07. Safety
│ ├── Guardrails
│ ├── AI Security
│ └── Prompt-Injection Defense
│
├── 08. LLMOps & Serving
│ ├── Model Selection & Routing
│ ├── Caching, Latency & Cost
│ ├── vLLM / TGI
│ ├── Quantization & Batching
│ └── Production Lifecycle
│
├── 09. Adaptation
│ ├── Fine-Tuning
│ ├── PEFT
│ ├── LoRA / QLoRA
│ └── Distillation
│
├── 10. Advanced
│ ├── Multimodal AI
│ ├── Knowledge Graphs
│ ├── AI App Architecture
│ └── Product Integration

Learn to ship AI systems, not just prompt models.

[Matt Pocock @mattpocockuk]

"I agree that software fundamentals matter. But which ones? In which order?"

My answer:

[Matt Pocock @mattpocockuk]

@atpaawej 1. Learn to read code
2. Learn to use the terminal
3. Learn how good teams prevent human/agent mistakes (types, tests, linting)
4. Learn how to structure your app to make your tests/types better (deep modules, seams, adapters)
5. Learn ubiquitous language from DDD

[Garry Tan @garrytan]

Children need to be teach-yourself-on-YouTube-maxxing

[elvis @omarsar0]

People keep asking why build a harness when Claude Code & Codex already exist.

Building even a small one changes how you use the big ones. You learn what breaks, what the model needs after a failure, and which knobs matter.

That knowledge transfers to every harness you touch.

[Matt Pocock @mattpocockuk]

AI has eaten tactical programming, so juniors need strategic experience in a low-blast-radius environment.

Here's one way to make that happen:

1. Give them responsibility over a large chunk of work
2. That work must be low stakes, but not no stakes - ideally an internal tool (AI makes these kinds of projects easy to justify)
3. Let them move fast and fail fast. Give them the same AI budgets as your senior engineers.
4. When failures happen, work with them to figure out what went wrong (learnings can also be pulled upwards into the rest of the org)

In a sentence:

Hire juniors. Give them work that matters. Watch them fail. Pick them up.

[Carlos De la Guardia @dela3499]

I wrote a kid-friendly summary of The Beginning of Infinity, by @DavidDeutschOxf.

It's 199 simple words:

[Swapna Kumar Panda @swapnakpanda]

SOFTWARE ENGINEERS ONLY...

Go GOD LEVEL in DSA in JUST 4 months. Crack any interviews easily:

[Ben Dicken @BenjDicken]

No human should ever have to implement a WAL, B-tree, LSM, or any other common data structure by hand going forward.

But, it's also just really freaking cool to learn how computer software and hardware works.

So why not keep learning?!

[Tim Ferriss @tferriss]

Bird by Bird is a lifeline during book-related crises of faith. One friend was on the verge of returning his advance to the publisher and calling it quits. Instead, I loaned him my copy of Bird by Bird. He regained his confidence, and his book became a New York Times bestseller.

[Jocko Willink @jockowillink]

Final Spin.
https://t.co/Cl9RlvyYnU

[Andrew Ng @AndrewYNg]

How have software engineering fundamentals changed with agentic coding? Here is our AI Engineering Skills map for software engineering fundamentals. https://t.co/cnRLj43DLs

[Navalism @NavalismHQ]

Babies and animals are interesting to watch because they aren’t self conscious at all.

@naval

[Navalism @NavalismHQ]

The tools for learning are abundant. It’s the desire to learn that’s scarce.

@naval

[DAN KOE @thedankoe]

Patterns I've noticed in people who aren't necessarily unhappy, but aren't going anywhere with their lives:

- Never learn anything new unless they're forced to
- Don't set goals unless their survival / finances make them insecure
- Talk about what's happening in the world rather than what they're working on
- Aren't aware of any of this, and making them aware doesn't hurts more than it helps

Hard place to be.

[Justin Skycak @justinskycak]

The reason that math is hard for most is the same reason that math is easy for some.