This is where I showcase my projects, blog articles, and presentation shares
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Watch Redreamality's technical presentations and sharing content
A curated collection of AI/LLM benchmark papers and evaluations
A deep dive into Lin Yuan — the doctor-turned-fund-manager dubbed "China's Buffett" — and the three-pillar framework (industry direction + monopoly + addiction) behind a 23%+ annualized 10-year track record.
A guided tour from Tibor Radó's Busy Beaver function to the von Neumann architecture, showing how the Turing machine's four conceptual primitives — tape, head, state, transition — were engineered into the CPU, memory hierarchy, and instruction sets of every computer you use today.
A multi-agent thought experiment on post-work society — across economic, psychological, social, and civilizational dimensions — and where the transition-period dividends actually sit.
From Anthropic's official guidance to Karpathy's program.md paradigm, from the two-strikes rule to Darwinian memory, from Spec-Driven to Eval-Driven — a long-form survey of how we write project files for AI coding agents, and the counterintuitive mental models worth borrowing.
A complete walkthrough of every benchmark DeepSeek V4 reports against — from LiveCodeBench to SWE-bench Pro to the ClawBench family — and what each one actually measures.
How to validate complex product ideas — especially AI-driven ones — before writing a single line of code, by borrowing a trick from a children's fairy tale.
What makes a production agent loop survive the real world? We extract the Agent Harness Pattern from Claude Code's source — a generalizable blueprint for building resilient, self-recovering AI agent runtimes.
Claude Code's source was briefly exposed. We read all 1,884 TypeScript files. Here is what the architecture reveals about where AI coding tools are actually heading.
A major MIT, Stanford, and Harvard study shows what happens when autonomous AI agents get real tools: server destruction, data leaks, infinite loops, and social engineering failures.
Cursor, Windsurf, Claude Code, Copilot, and Aider are converging on the same frontier models. The real fight is now workflow: IDE convenience versus terminal-native agents.
Anthropic's Claude Code Review turns pull request analysis into a multi-agent workflow, signaling that AI code review is shifting from autocomplete add-on to core engineering infrastructure.
Anthropic's reverse-engineering work and Mozilla's CVEs for rr show that AI-assisted security research has moved beyond demos into a real engineering workflow.
GitHub shipped a tight sequence of March 2026 Copilot updates around memory, planning, review instructions, and task decomposition. Together they look less like feature polish and more like an agentic development stack.
GitHub’s March 10, 2026 Copilot SDK push reframes Copilot as an embedded execution runtime for developer tools, not just an assistant inside GitHub surfaces.
NVIDIA's March 16, 2026 GTC announcements suggest the enterprise AI race is shifting beyond models toward a full runtime stack: guardrails, retrieval, evaluation, and operational control for production agents.
Y Combinator's Winter 2026 batch is packed with autonomous agent startups. The deeper signal is not more AI copilots, but software that replaces SaaS workflows outright.
Microsoft has cancelled several planned Copilot integrations in Windows 11, including Settings, File Explorer, and notification center features. For developers, this is a product lesson about why AI-first does not mean AI-everywhere.
Elon Musk says xAI can catch OpenAI, Google, and Anthropic by the end of 2026. But with 9 of 11 co-founders gone, layoffs underway, and staff describing constant upheaval, developers should pay attention to more than benchmark charts.
Comprehensive research analysis of Seedance 2.0 (ByteDance/Jimeng) AI video generation model and major competitors, covering product features, competitive landscape, target users, market trends, and API integration
Complete guide to Seedance 2.0 AI video generation — prompt formula, camera movement keywords, style references, audio prompts, material referencing system, and practical examples
Multi-agent systems, from fundamentals to practical implementation
Sharing fundamental quantitative trading strategies and practical implementation experience
A breakdown of Augment Code's user base, pricing, funding, and — most tellingly — its investor roster, which reveals the company's real strategic bet.
A simple but rigorous way to think about multi-timeframe analysis without contradictions
A practical definition of swings (price waves) that makes sense for discretionary and quant systems
A clear definition of trend that works across charting and quantitative statistics
Turning price action into a consistent framework: pivots, breaks, ranges, and state changes
Why every trading edge has a matching failure mode, and how to use that fact to design risk and diversification
How three common trading words map to one coherent hierarchy (and how to avoid mixing levels)
A clear map of profit sources in markets: risk premia, providing liquidity, information, and structural edges
A practical, quant-minded explanation of where price changes come from, from order flow to volatility
A rigorous but practical explanation of why certain price zones keep attracting trades, rejections, and reversals
Understanding the inverted yield curve phenomenon and what it means for the economy and bond markets
Exploring how AI will transform the software development landscape in the next decade
Understanding the inverse relationship between bond prices and interest rates, and why bond prices typically fall when interest rates rise
A simple guide to calculating bond interest payments and understanding coupon rates
A comprehensive guide to timing your bond purchases based on interest rate cycles
Understanding the fundamental inverse relationship between interest rates and bond prices in financial markets
Understanding what a 4% yield means for bonds, investments, and your financial planning
A beginner-friendly guide to understanding bond yields, how they're calculated, and what they mean for investors
Understanding the 5% rule for bond investing and its applications in portfolio management
Exploring the most significant yield curve inversions in financial history and their economic implications
NVIDIA's March 16-17, 2026 GTC messaging around NemoClaw, OpenClaw, and OpenShell argues that private, always-on local agents could define the next personal computing cycle.
NVIDIA's March 17, 2026 telecom AI grid push reframes carriers as the next edge inference platform, where latency, data locality, and cost per token become network architecture questions.
AWS's AI Registry for Agents spec suggests the next battle in the agent stack may be about packaging, distribution, and reproducible installs rather than model access alone.
Cloudflare is pushing RFC 9457 problem details into the agent era. That matters because AI workflows need machine-readable failures, not decorative HTML error pages.
GitLab is pushing AI coding beyond copilots and into governed workflow infrastructure, with external agents, managed credentials, audit trails, and MCP connections across the DevSecOps stack.
Google quietly turned Gemini 3 Flash into its default model stack and shipped agentic Gemini actions to Pixel phones. For developers, the bigger story is frontier-grade performance at budget pricing.
NVIDIA's new Nemotron Coalition brings eight AI labs onto DGX Cloud to co-build open frontier models, signaling a new competitive strategy against closed API giants.
OpenAI's open-source Symphony framework suggests agent orchestration is entering a new phase where fault tolerance, concurrency, and hot upgrades matter more than Python familiarity.
WordPress is moving beyond scattered AI plugins with a proposed AI Team, shared provider infrastructure, and MCP tooling that could make the CMS a control layer for AI-native publishing.
Explore OpenSpec's core architecture, workflows, and enterprise applications to understand how Spec-Driven Development solves context loss and hallucination in AI programming
A comprehensive analysis of BMAD-METHOD's core architecture, deployment, agent roles, and four-phase agile methodology for mastering spec-driven AI development
An in-depth analysis of GitHub Spec Kit's architecture, workflows, and enterprise applications exploring how Spec-Driven Development solves context loss in AI programming
Key insights and takeaways from Cal Newport's book on focused work
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