Kiro powers and Agent Skills in your development workflows
Leveling up your workflows with enhanced context using MCP, steering and hooks? Join us live as we show you how to use these ...
Leveling up your workflows with enhanced context using MCP, steering and hooks? Join us live as we show you how to use these ...
I've been building Pneuma, a desktop computing environment where software doesn't need to exist before you need it. There are no pre-installed applications. You boot to a blank screen with a prompt. You describe what you want: a CPU monitor, a game, a notes app, a data visualizer and a working program materializes in seconds. Once generated, agents persist. You can reuse them, they can communicate with each other through IPC, and you can share them through a community agent store. The
In 2023, I spent six months building a recommendation engine from scratch using vector search and manual indexing. Today, an entry-level dev can prompt a "weekend project" that looks 90% as good.While I admit that productivity is up, the "signal" for talent is disappearing. Just by looking at resume its incredibly hard to identify difference between a Vibe Coder and a Real Software Engineer. Resumes these days looks more or less similar, same type of skill set, same AI langua
When I start to program as a teenager, and it became my job in my early twenties, I was happy over the moon. I never made it my career because of money or prestige, teenagers rarely care about how much things pay in real life.Over the years, I've learned that coding is not the ultimate goal. People who get rewarded the most are not doing coding at all but doing aRcHiTecTure and DeSigN dOcuMents. Or better, manage the ones who write code. Purely writing code is seen as an intermediary step i
Most AI products are built around the same idea.Take a giant model. Add a prompt and hope it does the whole job. The AI equivalent of spray-n-pray.That works great for chatbots for creative outputs like code generation, website design and email writing. BUT, It breaks down fast for developer work that requires highly deterministic output. Think of OCR for KYC at banks or Audio recognition for patient-doctor notes.We have been training SLMs for specific tasks for a while now. During which we kept
The core problem I kept running into with hardware wallets: the private key exists as a persistent digital object inside a chip. It’s protected — but it exists. That’s the vulnerability. Protection fails; existence is structural. I built a different model. The private key is encoded as a geometric hole pattern in a titanium plate. A signing terminal reads the plate optically, derives the key transiently in volatile memory, signs the transaction, and discards everything. The plate doesn’t change.
I’m a solo founder. I built a Cognitive Infrastructure Substrate — pure algorithmic code, zero AI API calls inside, no OpenAI dependency, fully patentable. A discovery engine collides software primitives against each other and crystallizes viable configurations into production-ready code.It has autonomously discovered over $4.3B in software capabilities. I didn’t write what I’m sharing. The substrate found it.Neural Arbiter — CJPI 100 | Governance | $3M substrate valuationOne sentence: an AI dec
<img src="https://storage.googleapis.com/gweb-uniblog-publish-prod/images/March_2026_AI_Recap_social_hvvl.max-600x600.format-webp.webp">Here are Google’s latest AI updates from March 2026
You start a research task on your laptop, the network drops during a meeting, and when you open your phone to continue, the conversation is gone – you re-prompt, get partial duplicate results, and lose 30 minutes of work. The delivery layer dropped it. That's one of the most consistent problems teams hit when building AI applications.It's particularly acute in customer support, where a session belongs to the conversation - not to any single device, connection, or participant. An AI agent handles
Learn how you can use AWS services like AWS Backup and AWS Elastic Disaster Recovery (AWS DRS), along with AWS Resilience Competency Partner solutions like Arpio to implement powerful and comprehensive Disaster Recovery solutions. Resilience is the ability of your application to keep running even when “bad stuff” happens. A critical part of your resilience strategy is Disaster Recovery (DR). DR is what protects you against less frequent, but bigger faults like natural disasters, technical faults
Meta continues to lead the industry in utilizing groundbreaking AI Recommendation Systems (RecSys) to deliver better experiences for people, and better results for advertisers. To reach the next frontier of performance, we are scaling Meta’s Ads Recommender runtime models to LLM-scale & complexity to further a deeper understanding of people’s interests and intent.This increase in scale & complexity exacerbates a fundamental “inference trilemma”: the challenge of balancing the
<img src="https://storage.googleapis.com/gweb-uniblog-publish-prod/images/Email_SocialShare.max-600x600.format-webp.webp">Here’s how to change your Google Account username (and how to change your Gmail address) in a few simple steps.
Most teams building AI agents start with HTTP streaming. It's the right starting point. Every major agent framework defaults to it, it gets tokens on screen fast, and for a single-user prompt-response interaction it works well.The question is when it stops being enough - and how to recognise that before it turns into user experience problems, engineering waste, and technical debt that constrains what your product can do.Over the past year, I've spoken with over 40 leading AI companies building p
HTTP streaming – the default transport underneath every major agent framework – was never designed for sessions that survive a tab close or hand off cleanly between participants. Two failures surface consistently in production CX products because of this. Both generate support tickets about conversation state and prompt quality. Both trace to the transport layer.The scenario that illustrates them: a customer contacts support about an order that's partially shipped and partially stuck. The AI age
Meta is continuing its long-term roadmap to help the construction industry leverage AI to produce high-quality and more sustainable concrete mixes, as well as those exclusively produced in the United States. Concurrent with the 2026 American Concrete Institute (ACI) Spring Convention, Meta is releasing a new AI model for designing concrete mixes – Bayesian Optimization for Concrete (BOxCrete), as well as the foundational data used to develop award-winning concrete mixes.Meta’s open source model
This post is cowritten with Yuri Brigance, and Usman M. Khan from Aigen. Aigen builds autonomous robots designed to help farmers remove herbicide-resistant weeds and improve crop yield through AI-driven technology. These robots operate without chemicals, using renewable energy, and provide real-time, field-level data to enhance decision-making. Using advanced computer vision AI, Aigen’s robots autonomously identify and remove weeds without harming crops, giving farmers an eco-friendly, cost-effe
Every major layer of the AI stack now has a name. Model providers - OpenAI, Anthropic, Google - handle inference. Agent frameworks - Vercel AI SDK, LangGraph, CrewAI - handle orchestration. Durable execution platforms like Temporal make backend workflows crash-proof.Between the agent and the user's device, there is nothing comparable. The stateful connection through which the agent and user actually interact - the session itself - has no dedicated layer, no recognised category, and no purpose-bu
Very excited to share Anvil. I built Anvil to take back control when working with parallel coding agents. It comes with one click worktree isolation, and first class spec support.Claude Code and similar coding TUIs are very eager to get into writing code, even before their human baby sitter fully understands the implication of what they are about to build.The core insight with Anvil is that it is much easier to write high quality code which matches the author's intent after iterating on an
Mnemosyne: A blueprint for computational pluralism via physical laws.-Security: Establishes a 10^38 Joule physical floor (kappa >= 804 bits) derived from Landauer’s Principle and the Margolus-Levitin limit.Infrastructure: Targets 2GB RAM edge devices using BFT-MESI cache coherence.-Verification: Formally specified in TLA+; preliminary TLC verification completed for minimal configurations (n=4, f=1).-Economics: Proof of Useful Work (PoUW) for socially beneficial AI compute.-Current Openings:Se
I constantly ask Gemini/ChatGPT/Claude about books on a certain topic, then ask the llm to give me a summary of the book its chapters - this helps me: 1. keep the llm grounded as a real expert (instead of saying pretend to be an engineering expert, give it a distributed systems book and then ask opinions on it) 2. helps me discover and buy books! Once i go through book concepts and chat with llm about it, i'm more convinced to buy it and dig deeper on low level on itSo i built an