TrendPulse

Call it a startup with a sole founder and a very large seed round, but what's next is less clear.

Reliance is weaving AI into telecom services used by more than 500 million people.

You don’t have a naming problem. You have a 40‑minute decision problem. Here’s a practical, timer-based method to name your SaaS in 2026, without spiraling into a 3‑week Notion rabbit hole. Ground rules for 2026 A few constraints you can’t ignore: .com is crowded. There are around 157 million .com domains registered globally as of 2026, so the obvious one-word .com you want is almost certainly taken or expensive. What is .com domain Domains cost real, recu...

"Intelligence isn't about searching everywhere—it's about knowing where not to search." Artificial Intelligence is often associated with neural networks, large language models, and autonomous systems. But long before modern generative AI, computer scientists were solving a much deeper question: How do intelligent systems make decisions efficiently? Whether you're building search algorithms, recommendation systems, autonomous robots, or distributed systems, the architecture of int...

The next Model Context Protocol specification, 2026-07-28 , is the largest revision since the protocol launched. The release candidate locked on May 21, 2026, and the final spec publishes on July 28. It contains breaking changes to transport, authorization, and how tool schemas are handled. A server that is correct against 2025-11-25 today is not broken. Nothing here is a present-tense vulnerability. But several of these changes are security properties, not just compatibility ones — reques...

Hey everyone, I've been deep in prediction market infrastructure for a while and just open-sourced a market maker bot designed for CLOB-based prediction markets like Polymarket. What it does: Quotes both sides of a binary market automatically Adjusts spreads based on order book depth and volatility Manages inventory risk to avoid getting stuck on the wrong side of a resolved market Built on top of Polymarket's CLOB API with Gnosis Safe / EOA wallet support on Polygon The co...

(or: How I Turned My Laptop Into a Lightsaber for the Market) The Quest Begins (The “Why”) Ever stared at a blinking cursor at 2 a.m., wishing you could make your laptop do the heavy lifting while you chased dreams (or just caught up on sleep)? I was there, scrolling through Reddit’s r/investing, watching folks brag about “algo‑trading gains” while I was still manually refreshing Yahoo Finance like a peasant in a medieval market. One night, after yet another failed attemp...

A field guide to the practice that's reshaping how software gets built with AI agents. TL;DR — Spec-Driven Development (SDD) makes a precise, executable specification the source of truth and treats code as a generated, verifiable artifact. The spec declares intent ; the code realizes it. In 2026 it went mainstream because AI agents are great at writing code and terrible at guessing what you meant. Jump to: Why now · Specs vs. executable specs · Maturity model · Workflow · Too...

As developers, we’ve all been there: you’re building a hobby project, a side hustle, or a microservice, and you need object storage. You look at AWS S3 or dedicated cloud providers, and the costs start adding up. Meanwhile, most of us have hundreds of gigabytes of idle, wasted space sitting in our personal Google Drive, Dropbox, or Mega accounts. I wanted to find a way to use that personal cloud storage programmatically—specifically as an S3-compatible bucket—without paying premium storage fe...

Hey dev.to community! 👋 Over the last few months, juggling my roles as a Project Manager, Scrum Master, and lead for QA, Support, and Documentation has been a wild ride. The sheer speed of "vibe coding"—a paradigm shift where the primary role of the developer transitions from manual code construction to high-level intent orchestration—is incredible. Tools like Cursor, Replit Agent, and Google Antigravity allow us to scaffold entire microservices in minutes. However, while this transition o...

Durante mucho tiempo asocié el desarrollo de software con programar funcionalidades: crear entidades, armar controladores, conectar una base de datos, validar formularios y hacer que una aplicación responda correctamente. Sin embargo, durante el Trabajo Final de la asignatura Desarrollo de Aplicaciones Web , entendí que programar es solo una parte del problema. El verdadero desafío aparece antes de escribir código: decidir qué arquitectura conviene, por qué conviene, cuánto cuesta, qué riesgos...

The invoice arrived on a Tuesday morning. $340. For a side project I'd built in a weekend. A small LLM-powered summarization tool — users paste text, model returns a summary. I'd done the math before launching: roughly $0.002 per request, ~500 requests/day, around $30/month. Totally fine. What I hadn't accounted for: system_prompt_tokens = 800 requests_per_day = 2000 # not 500 — it went viral in a group chat input_price_per_1M = 2.50 # GPT-4o daily_cost = (800 * 2000 / 1_000_000)...

A finance bot kept issuing refunds in a loop because nobody built a way to stop it. Clean code. Sound logic. No off switch. A small bug became a long night. Here is the opinion most teams do not want to hear. Building the agent is the easy 80 percent. That off switch is the 20 percent that decides whether you can ship it at all. We celebrate the wrong milestone. Picture the demo where the agent books the meeting, writes the email, updates the record. That part is genuinely fun to build ...

The morning my own file lied to me Wednesday, May 21, start of session, coffee next to the keyboard. I ask the agent where we stand on the DEV.to series. Clean answer, articulated, "Four articles on stand-by, ready to publish." I reread. Half a second of unease, because I think I saw two or three of them go through DEV.to last week, but I slept in between and I'm no longer sure. I type the question that changes everything, "Are you sure articles remain to publish?" The agent re-queries t...

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Learn why finishing small game projects teaches more than endlessly polishing one big idea.

Most developers understand the surface layer: user enters a password, system checks it, access is granted. That mental model breaks the moment you need to add MFA, support passkeys, implement device trust, or explain to a security auditor what telemetry your login page collects.

Wizard Ecosystem: The free, AI-powered alternative to Google Workspace. Browser, Mail, Calendar, Chat, Search, Notes, and AI — all in one place. Built by a 12-year-old. 🧙

A search feature gets slow not because you lack a search engine, but because the access pattern outgrew the data model. To fix it before buying new infrastructure, you climb a ladder of cheaper, reversible changes: single round-trip paging, index hints, full-text and suffix indexing, and parallel queries, weighing each option's price along the way.

Most teams building AI agents default to running every step through the same frontier model. That is the most expensive possible architecture and often not the best-performing one either. The Plan-and-Execute pattern fixes this by separating the work that actually requires expensive reasoning from the work that does not. A capable planner model breaks the task into steps. Cheaper executor models carry those steps out. In practice this means routing 70 to 90% of your token volume to models costin...

I realised descriptive dashboards were not enough because people still needed analysts to interpret the numbers. By designing around decisions, adding context, moving logic into the data layer, and reducing visual noise, I built systems that reduced friction between insight and action.

An exposed energy-themed honeypot gets discovered in under an hour, then faces continuous brute force, web scanning, and protocol-aware Modbus reconnaissance, with zero write or control attempts. Part 3 turns those findings into defence. The same structural controls that stop commodity scanning also shrink the targeted tail: keep OT protocols and management planes off the public internet, block egress by default, remove default credentials, segment IT from OT, and log behaviour instead of bare p...

A randomized trial says AI may make experienced devs slower while they feel faster — and the gap may be narrowing as tools improve, but the perception/reality bias is still real. A survey of 319 knowledge workers says AI shifts thinking from synthesis to stewardship; a separate 666-person study found a strong negative correlation between AI use and critical thinking. The new HBR/BCG "AI brain fry" study put hard numbers on the agent-supervision burnout pattern. The neuroscience offers one plausi...