AI & ML - CodeNest

Tree of Thoughts and MCTS for LLMs: What Happens When You Stop Making the Model Guess Once

Hello, I'm Shrijith Venkatramana, and I'm building LiveReview — a blast-radius aware AI code review built for your business-critical systems. Star us to help devs discover the project, give it a try, and share your feedback to help improve the product. Most LLM applications work like this: pr

AI & ML 09-06 32 DEV Community

Claude Fable 5 and Opus 4.8: The Complete 2026 Guide

Claude Fable 5 has quickly become the center of discussion among software engineering teams since its early June 2026 launch. The model is Anthropic's most powerful reasoning engine to date. Anthropic designed the model specifically to handle complex coding and autonomous agentic workflows. This gu

AI & ML 09-06 23 DEV Community

Why LLMs Should Never Touch Money Directly: Building an AI Payment Recovery Agent Solo

How I built REVA for Track 3 of the Razorpay AI Buildathon 2026—and why deterministic guardrails matter more than AI autonomy when money is involved. The Problem I Wanted to Solve Building for Track 3 of the Razorpay AI Buildathon 2026 as a solo developer came with one obvious challen

AI & ML 09-06 22 DEV Community

How I Turned a Research Paper into an AI Skill with NotebookLM

I wanted to create a reusable AI skill, but I did not want to write vague instructions based on guesswork. I wanted the skill to have a clear foundation. So I started with a research paper and used NotebookLM to understand its main ideas before turning them into a practical skill.md file. Here

AI & ML 09-06 32 DEV Community

The Advice Was "Build on Unique Data." Mine Was a House.

A response to Marina Wyss's How I'd Learn Machine Learning in 2026, from someone who arrived at the same checkpoints from the construction side. Marina Wyss wrote that piece and the part that stopped me was not the curriculum. It was her argument that a hiring manager is not looking for evidence th

AI & ML 09-06 19 DEV Community

Harness Score 1.6.4: Safer Scans, Broader CI, and Trustworthy Docs

AI coding agents do not work in a vacuum. Their results depend on the context files, rules, skills, hooks, tests, CI pipelines, and safety controls that surround the model. That surrounding system is the harness: the part of an agentic workflow that a team can actually design, version, test, and imp

AI & ML 09-06 18 DEV Community

IA Proativa e IA Geral (AGI), os próximos passos do uso da IA em Tecnologia

Lançado no dia 03/09, o GPT-6 Astra marca segundo a OpenAI, o início da era de IA 'AGI', isto é, de agentes capazes de usar recursos pensados numa hipotética Inteligência Artificial Geral (AGI na sigla em inglês). Apesar do termo AGI ainda não ter uma definição clara e coeza, o presidente da OpenAI,

AI & ML 09-06 18 DEV Community

I Violated an API Contract by Fixing a Timeout Bug

Apparently Contracts Should Be Honored When I think of contracts, I think of scary documents that limit my freedom, usually in exchange for something I want. Documents like EULAs, user agreements, divorce papers, and prenups are just a few examples. However, these contracts also provide a sense o

AI & ML 09-06 16 DEV Community

Fill Existing PDF Forms from n8n Without Rebuilding the Template

Many document automations generate a new PDF from HTML. That is the right tool for invoices and reports you design yourself. It is the wrong tool when a customer, carrier, government office, or employer requires its existing PDF to keep the same layout. The workflow below handles that second case:

AI & ML 09-06 15 DEV Community

Batch Processing: From Unix Tools to Distributed Systems

Much of the traditional software operations we deal with are online, we click a button, wait for a moment, and the transaction or operation is completed. But there is a big area that deals with software operations that require offline processing. For example, background processing of jobs, e.g., Op

AI & ML 09-05 18 Dev.to (EN Zone)

Why Most AI Agents Fail Long Before the Model Does

The agent did not fail because the model was stupid. It failed because a CRM tool returned a 502, the agent retried, created two support tickets, read a stale knowledge-base article, filled the context window with stack traces, and then told the customer everything was fine. When teams see this, th

AI & ML 09-05 23 DEV Community

The confused deputy, or why "just forward the token" breaks your MCP server

Here is a failure that does not look like a bug in code review, passes every test you wrote, and quietly hands an attacker your privileges. It is called the confused deputy, and it is the reason "just forward the token" is one of the most expensive shortcuts you can take in an MCP server.

AI & ML 09-05 22 DEV Community

AI Meeting Notes That Capture What Was Decided and What Comes Next

AI agents can turn raw transcripts into reliable follow-up records with decisions, action items, and the context needed to move work forward The Limitation of Basic Meeting Summaries Many AI meeting summaries arrive in email or chat, get skimmed once, and disappear. The summary might be

AI & ML 09-05 15 Dev.to (EN Zone)

Can Your AI Use What It Remembers?

An assistant correctly recalls a user's tree-nut allergy. Given a request for macarons, it supplies an almond-flour recipe without applying that allergy to the user. This is a recorded example from InMind, a July 2026 study of agent memory, using xMemory. The evaluations ask two different things: c

AI & ML 09-05 17 Dev.to (EN Zone)

Gemini 3.8 Flash: Benchmarks, Price, Cyber - Proje Defteri

TL;DR: Gemini 3.8 Flash in 30 seconds Gemini 3.8 Flash landed on September 2, 2026, three weeks after 3.7 Flash. That is the third Flash release in three months. Price did not move: $0.75 input, $3.75 output per million tokens. The promo ends December 31, 2026, then it doubles. A second model shi

AI & ML 09-05 16 Dev.to (EN Zone)

A Guardrails Library That Publishes Its Misses

Ask a guardrails library how often it is wrong and you will usually get silence, or a benchmark of how fast it is. That is the gap jamjet-guardrails was built into. Nine deterministic checks for LLM input and output, zero runtime dependencies, and a published precision and recall figure for every o

AI & ML 09-05 18 DEV Community

EU Cyberbullying Resolution Signals Stronger Platform Responsibility, Not a New Law

The European Parliament has adopted a resolution calling for targeted criminal provisions and more effective platform responsibility to address cyberbullying and online harassment. The move is a significant political signal that EU lawmakers see the problem as increasingly cross-border. It is not, h

AI & ML 09-05 23 Dev.to (EN Zone)

Interpretability Built an Instrument to Prove a Signal Is Actually Used. Agent Memory Has Nothing Like It.

A model can contain a decodable signal and not use it to produce its answer. That sentence is the whole problem with interpretability, and it took me an embarrassingly long time to feel its weight. A linear probe recovers a concept from an activation. A sparse autoencoder isolates a direction that

AI & ML 09-05 22 Dev.to (EN Zone)

The hardest label in our dataset is the one where nothing happened

Four times a year, a public company gets on a call with analysts and says what it intends to do next. A margin it expects to reach. A plant it expects to commission. A growth rate it expects to hold. These are the most concrete forward statements a company makes outside a filing, and they are made o

AI & ML 09-05 23 Dev.to (EN Zone)

🎨 Software Engineering in the Age of AI: From Code to Craft

AI is no longer just a helper in development — it’s becoming a core collaborator. With this shift, the role of a software engineer is evolving. What defines great engineering today isn’t memorizing syntax or configuring systems; it’s curiosity, observability, patience, and the ability to steer conve

AI & ML 09-05 20 DEV Community