Zencoder

Haiku 4.5 is out. The model is remarkably capable — just six months ago, this level of performance would have been state-of-the-art on our internal benchmarks. Now it runs 4 times faster than Sonnet 4.5 at one third of the cost. This leap in performance and efficiency unlocks an entirely new set of use cases. It’s exciting to see frontier-level intelligence becoming more accessible.

Most of us started with AI coding agents the same way we search Google: type a vague prompt, hope for magic. That works fine for toy apps — but when it’s time to ship production-grade systems, “vibe-coding” breaks down fast. In this webinar, we’ll talk more about Spec-Driven Development (SDD): a practical methodology that treats AI coding agents like literal-minded but powerful pair programmers. You’ll learn how SDD transforms chaotic prompting into a structured process with: - Upfront clarity through comprehensive specifications - Plans that respect your existing architecture and constraints - Tasks broken into testable units - Implementations that stay consistent across sessions We’ll walk through a real-world example: building a production-ready multi-channel notification system (email, SMS, in-app) with retries, analytics, and compliance requirements. By the end, you’ll understand not just the what but the how and why of spec-driven development — and how it can make AI-assisted coding a reliable part of your production workflow.

Anthropic's Haiku 4.5 is now available on Zencoder – matching Sonnet 4's performance on coding, agentic tasks, but at substantially lower cost and faster speeds. Performance highlight: 73%+ on SWE-bench Verified: Delivers what was state-of-the-art five months ago in their most efficient package When to use Haiku 4.5 vs Sonnet 4.5: Sonnet 4.5: Frontier coding agents, critical reasoning tasks Haiku 4.5: Parallelized execution, sub-agents, high-volume operations Practical applications: • Fast incident response where speed directly impacts resolution time • Incremental improvements at scale (refactoring, test generation, code reviews) • Agentic workflows with multiple sub-agents running in parallel • Budget-sensitive deployments that still need strong intelligence Read about the release here 👇 https://lnkd.in/eQgTuBC3

Agents weren't ready 6 months ago. Models couldn't handle real work. Building with agents felt too early. Everything changed when the models caught up. Join us with Aykhan from Zencoder's Data and Agents team: → Why agents are now essential to the developer stack → The turning point that made autonomous coding real → How your workflow changes with Git, IDE, and Agents If you're still treating AI like fancy autocomplete, this conversation will shift how you think

🤔 Wondering if Zencoder is where you belong? At Zencoder, we've discovered that success isn't just about expertise, it's fueled by curiosity, genuine passion for transforming how AI helps developers work, and the energy you bring to collaborative problem-solving. We asked our team across engineering, product, and leadership: "What makes someone truly thrive here?" Their honest answers reveal what it's really like building the future of AI-powered development. Watch below 👇 #TeamZencoder #StartupLife #TechJobs #AIStartup #JoinOurTeam

How do you keep AI agents on track across long-running executions? Today, we’re publishing a practical guide on Spec-Driven Development — a framework for ensuring that agents stay consistent, goal-aligned, and effective across multiple sessions while standardizing workflows across engineering teams. Read the full guide here 👇 https://lnkd.in/gsjkBdWF

As engineering teams go AI-first, one challenge rises above the rest: how do we stay secure and compliant while moving at AI speed? In this episode, we’ll unpack the security and compliance questions every AI-driven team is facing today: 🔐 The evolving security risks when AI becomes part of the toolchain 📜 Compliance challenges in regulated industries adopting AI ⚖️ Balancing innovation with data protection and governance 🛡️ Best practices to keep engineering both AI-powered and secure This is more than a conversation about AI — it’s about building trust, resilience, and compliance into the next generation of engineering practices.