Systems | Development | Analytics | API | Testing

I Let AI Audit My LinkedIn Strategy (Here's what happened)

Mar 24, 2026 By Databox: Modern BI Software In Databox
If you’re consistently posting on LinkedIn, the hard part isn’t getting data — it’s analyzing it. Most people review posts one by one, compare impressions manually, and try to “spot patterns” by eye. That’s slow. And it makes strategy reactive. In this walkthrough, Kamil Rextin, founder of 42 Agency, uses the Databox MCP with Claude to run a fast, AI-driven analysis of his LinkedIn performance — the kind of first-pass review you’d normally assign to a junior analyst.
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tricentis

Why 95% of AI pilots fail - and what it takes to scale in the agentic era

Mar 24, 2026 By Lizzie Stokes In Tricentis
Last August, MIT released a landmark report that confirmed what many enterprise leaders had started to fear: most AI pilots are failing. After reviewing hundreds of AI initiatives, researchers found that 95% of generative AI pilots failed to reach production or deliver measurable results. The headline quickly hardened into a cliché: AI doesn’t scale.
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speedscale

FastAPI Testing: Mock LLM APIs for Free

Mar 23, 2026 By Ken Ahrens In Speedscale
Testing a FastAPI app that calls OpenAI, Anthropic, or Gemini gets expensive fast. The problem is not just the API bill in production. It is all the repeated traffic in development: prompt tweaks, CI runs, regression checks, and the load tests you keep putting off because every run burns tokens. Hand-written mocks do not help much once the app is doing multi-step LLM work.
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katalon

AI in Software Testing: The Triple Threat to QA in 2026

Mar 23, 2026 By Huyen Nguyen In Katalon
It is Monday morning. Your VP of Engineering just forwarded a company-wide memo: every team needs to demonstrate AI adoption by end of quarter. At the same time, you learned last week that your QA budget was trimmed by 15%, because leadership assumes AI will "make testing more efficient." And your developers? Thanks to Copilot, Cursor, and Claude Code, they are now shipping 76% more code per person than they were two years ago.
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How leading AI companies really build: lessons from 40+ engineering leaders

Mar 23, 2026 By Ably Realtime In Ably
What does it actually take to ship Gen 2 AI experiences to real users at scale? Matthew O'Riordan, CEO of Ably, shares insights from conversations with 40+ engineering leaders — including at unicorns and public corporations — on where AI delivery breaks and what production teams are doing about it. Topics covered: Timestamps.
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appian

How to Reframe Modernization for the AI Era

Mar 23, 2026 By Rachel Nizinski In Appian
IT leaders today are in a high-stakes gridlock between the pressure to invest in new AI solutions and legacy systems that aren’t equipped to support them. With the pace of work today, long modernization projects are often untenable. They disrupt your workflows. They use up your team’s resources. And they sometimes fail to deliver results. So how do successful organizations move forward? They rethink their approach.
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speedscale

The Hidden AI Bill: Why Non-Prod LLM Costs Spiral

Mar 20, 2026 By Ken Ahrens In Speedscale
Most teams know they are spending money on AI in production. Far fewer realize how much they are spending outside production. It’s easy to get lost as you evaluate which model has the best responses, is fast enough, and cheap enough to run in production. That is because the AI bill usually shows up as a giant blob. It is easy to see the total.
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hitachi vantara

What CTOs Need to Know About Modern AI Storage

Mar 20, 2026 By Liam Yu In Hitachi Vantara
As organizations scale their AI initiatives from experimentation into production, CTOs face a pivotal architectural challenge as storage emerges as one of the most common—and most expensive—constraints. While organizations continue to invest aggressively in GPU compute, studies consistently show that infrastructure inefficiencies outside the GPU account for the majority of wasted AI spend.
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