4 posts tagged with "python"

Arthur is 75. He lives alone in a cold, terraced house in Greater Manchester on a basic State Pension of just under £210 a week. When his dual-fuel energy bill climbed again this winter, he started turning off his heating at 4pm and eating one hot meal every two days.

He had never claimed a means-tested benefit in his life. He assumed benefits were "for other people," that applying meant handing over his bank statements to an invasive algorithmic portal, and that even if he qualified, it would only be for a few pounds.

He didn't know that his weekly income placed him £15 below the Pension Credit guarantee threshold. He didn't know that claiming that £15 a week would automatically passport him to a £150 Warm Home Discount rebate, an 85% Council Tax Reduction from his local authority, a free TV licence (available to Pension Credit recipients aged 75 or over), and support with NHS dental and optical costs. Across the year, his unclaimed entitlement totaled more than £4,200.

Arthur isn't an isolated case. He is one of 880,000 eligible UK pensioners missing out on Pension Credit, part of a wider £23 billion mountain of unclaimed benefits and support schemes every year across England.

The message arrived on a Thursday evening. Forwarded twice already. The text looked official: a government energy rebate notification, a pending payment of £400, a link to "verify your bank details before the payment window closes Friday." The sender was her son's colleague. Nobody had checked where it came from first.

She forwarded it to her son before clicking. He was about to say it looked fine. Then he noticed the URL: gov-rebate-energy.co.uk. Not gov.uk. Not energy.gov.uk. A registered domain, clean design, HTTPS padlock, professional enough to pass a quick read. He told her not to click. She'd been one browser tab away from entering her sort code and account number into a credential-harvesting form.

This near-miss required one thing: a second person who knew what to look for. Most people don't have that. That's what I'm trying to build.

She sent 47 applications in June. Got three responses — two automated rejections and one screening call for a "graduate entry" role that turned out to require three years of commercial Python experience. She kept a spreadsheet. Most rows stayed blank.

This isn't a personal story of bad luck. It's what the ONS is measuring when it reports that employment concern among UK adults rose from 31% in June 2024 to 54% in June 2026 — the highest level since the survey began. The headline is anxiety; the substrate is a market where 14% of entry-level postings disappeared year-on-year, ATS systems silently discard CVs against narrow keyword thresholds, and job aggregators cheerfully surface the same role six times from six different scrapers.

The current generation of AI job tools makes this worse. They optimise CVs to game ATS keyword matching. They automate bulk applications, violating employer terms of service. They give candidates the dopamine hit of "sent" with no honest signal of fit.

I built the UK Graduate Career Navigator this week as a direct counter to that. It has Claude on the inside. It is not trying to do more than a candidate should trust an AI to do.

A 999 call comes in: a 3-storey building is on fire, casualties are reported, and High Holborn is gridlocked. The Incident Commander has roughly 90 seconds to answer four questions. Which hospital can take burns patients — and is it under pressure? How many pumping appliances does the NFCC minimum require for a multi-storey structural fire? Which traffic corridor can the ambulances actually reach? And does this cross the threshold for a formal Major Incident declaration?

Which agentic pattern you use to support that decision changes everything — not just how fast the answer arrives, but whether the answer is auditable, protocol-compliant, and safe to act on without a human double-checking it.

This is Part 2 of the JigsawFlux series on open-source agentic frameworks. Part 1 compared LangGraph, CrewAI, and AutoGen at the framework level. Part 2 puts eight specific reasoning patterns — ReAct, ReWOO, Plan-and-Execute, Reflexion, Hierarchical, DAG, Network/P2P, and Consensus — through the same incident and measures what each one actually does. The full source is at github.com/JigsawFlux/agentic-patterns.