Building a basic AI agent is easy. Engineering the harness so it survives production is the real challenge.
I wrote a complete guide on learning LangChain’s Deep Agents framework from scratch, by building up to an autonomous competitive intel system.
Link below.
I've been interested in loss landscape visualization for a while now, and I finally completed writing a detailed post about it, and published it on @towards_AI
link: https://t.co/ac9SSitFkQ
#AI#NeuralNetworks#LossLandscapes
@levelsio AI will most definitely replace more and more companies. It's already happening in the service sector.
While we haven't reached total industry disruption yet, AI is already accurately performing tasks that used to sustain entire small-scale firms.
Everything explained + working code you can run in Colab.
Perfect if you want to understand how agents *actually* work 👇
Part 1: https://t.co/dupNw73UmU
Part 2: https://t.co/dupNw73UmU
I just finished a 2-part guide on building AI agents from scratch with Python 🧵
Part 1: Core agent with tools, type-safe outputs, ReAct pattern.
Part 2: Long-term memory, human-in-the-loop, observability, error recovery.
2025 in AI, Summed Up
From Nobel wins to viral AI art, agentic coding, and record-shattering apps, 2025 reshaped the AI landscape.
For a full AI rewind of 2025, check out the blog here: https://t.co/ExAXozoSBR
12/12 Will The AI Bubble Burst? (December)
Investors worry about “obscure overlapping arrangements” in the AI economy, echoing 2008 financial fears.
OpenAI is reportedly raising again, potentially valuing the company at $830B.
Experts debate if the AI bubble has burst.