Reading list
129 unread · 19 fetched and readable offline · built 5/9/2026
BUILD: Agent Fundamentals
Read these first if new to agents. Foundational patterns + 2026 landscape overviews.
- Why We Thinklilianweng.github.io
Lilian Weng on inference-time reasoning, chain-of-thought, scaling test-time compute
clean spectrum definition; reframes the landscape
Anthropic eng (skim — already discussed)
"tutorial hell is comfortable; world demands systems" — opinionated 2026 stack overview
opinionated triage of the 2026 agent landscape
builder's guide to agent stack components
UX/interaction patterns for agent systems
multi-model routing as default, not afterthought
PostHog: 5 hard-won lessons
Hamel Husain: harness IS data science
battle-tested practitioner advice
Sarah Wooders (MemGPT/Letta)
Harrison Chase: 3 layers of learning
reframes skill system
failure mode taxonomy
Qwen team lead on agentic RL
LangChain team on behavioral evals
companies converging on self-improving agents
open-source self-improving loop
self-healing deploy pipeline
BUILD: Agent Harnesses
W18+ priority. Want to build with OpenClaw and/or Hermes. ~20 articles, dominant theme of W17 X-triage.
blocmates intro to Hermes
LangChain's hosted alternative
practical SDK walkthrough
action space construction
direct reverse-engineering walk
synthesis of OpenAI/Cursor/Anthropic blogs
best opener (per the learning map)
control theory framing
backend metaphor
same metaphor, different angle
calcsam vs dexhorthy debate
frameworks vs harnesses
three layer model (weights → context → harness)
evals-driven harness improvement
synthesis of Q1 2026 OpenAI/Cursor/Anthropic reports
Bell Labs framing
- Effective harnesses for long-running agentsanthropic.com
Anthropic eng on patterns for sustained agent work
Anthropic eng on production harness architecture
context efficiency in Playwright CLI
Harrison Chase
- Effective context engineering for AI agentsanthropic.com
Anthropic eng: definitive context engineering reference
pre-built configurable harness
sandboxes, controllable harness, memory control
BUILD: Autoresearch
You saved this topic 8 times. Read the primaries.
Primary: 20 improvements, 11% speedup
Primary: 3-file architecture
Best analytical breakdown, 5 lessons
- Karpathy's Autoresearch for PMs: Complete Guidenews.aakashg.com
Non-ML applications
production proof
MLX optimization results
extends AutoResearch to subjective domains, co-written with Hermes Agent
open-source Deep Research stack beating OpenAI/Gemini/Perplexity
BUILD: Multi-Agent & Orchestration
- How we built our multi-agent research systemanthropic.com
Anthropic eng on the Research feature's multi-agent architecture
production agent, 250% conversion lift
Swarm via tmux/worktrees
multi-agent coordination
directly relevant to your setup
CEO/worker hierarchy
LLM Council deliberation
BUILD: Agent Memory & Personalization
Shpigford: USER.md + MEMORY.md (for David)
adversarial debate for sycophancy
SOUL.md/MEMORY.md/DREAMS.md
first-principles walk through agent memory
full guide on why agents forget + how to fix
memory systems for LLMs forget exactly like brains
multi-agent memory sharing
bottom-up map of where Claude-Mem sits in the agent stack
BUILD: MCP & Tools (MCP-proper only)
See `research/reading-notes/build-agent-context-and-tools.md` for the filesystem-as-tools split that came out of W16-W17 reading.
- GitHub - 1st1/lat.md: Agent Lattice: a knowledge graph for your codebase, written in markdown.github.com
markdown knowledge graph + MCP server
server design, OAuth with CIMD and vault patterns
Anthropic eng: tool design principles for agent reliability
BUILD: Practical Setups
non-dev built full CoS in 36 hours
closed-loop agent architecture
3-layer design harness for non-designers
- Prompt Engineeringlilianweng.github.io
Lilian Weng
- An update on recent Claude Code quality reportsanthropic.com
Anthropic incident postmortem on a model degradation root cause
BUILD: AI/ML Deep
Papers + technical posts on RL, neural computers, model architecture. Slower reads, lower priority than agent harnesses for active focus.
Unsloth practical guide
implementation walkthrough
explainer for the MIT RLM paper
Meta paper trains NN to simulate computer
FOUNDER/LIFE: GTM & Distribution
growth playbook
itsalexvacca, 300+ companies experience
shannholmberg
sellable workflows
DeRonin runs 10 socials, no manual posts
Chatbase $9M ARR playbook
agency-to-SaaS playbook
agency-to-SaaS $10M exit math
FOUNDER/LIFE: Org & Capital
30 lessons. Game C aligned.
Dorsey + Botha: Block's AI-native org
a16z on building firms vs funds
pod model for AI agencies
Hashimoto on building blocks vs apps
PE firms as ideal AI niche
Hebbia CEO
FOUNDER/LIFE: AI-Native Strategy
99% AI code, what they learned
Sequoia opportunity map
what nobody is building yet
itsalexvacca on the Sequoia thesis
models good enough, the bottleneck is elsewhere
a16z
5 moats that survive AI
- Introduction - SITUATIONAL AWARENESS: The Decade Aheadsituational-awareness.ai
Aschenbrenner: AGI timeline
Ramp VP: bitter lesson for agents
FOUNDER/LIFE: Identity & Life
- How to Do Great Workpaulgraham.com
Paul Graham
daniel_dhawan, SF social capital practical
practical for May 15 move
Innovation/Capital/Deflation first principles
whole company on one laptop
Dan Koe on generalism
bootstrapping manifesto
Yacine
"you can just build things"
FINANCE: For Holding, David, Atlas
Quant models, financial AI, investment strategies
Daloopa CEO
Monte Carlo, Kelly, copulas with code
IR = IC * sqrt(N)
Kelly, Bayesian, Nash with code
Daily pre-market for Holding
Claude wealth management plugin
TurboQuant economics
- A decoder-only foundation model for time-series forecastingresearch.google
Google's TimesFM
2.55 Sharpe, 2.79 Sortino, $50M+ capacity, no human PMs
private markets liquidity (Atlas-relevant)
STATISTICS: Foundational Methods
Probabilistic thinking, sampling, dependence structures. Feeds quant work + JL/TurboQuant lineage.
Wiecki, intuitive intro to Metropolis-Hastings
Wiecki, dependence beyond correlation