Techliance

Pakistan's Federal Budget 2026-27 extends the 0.25% concessionary tax rate on IT export earnings through June 2029 even as the IMF pushes to phase out Special Technology Zone incentives by 2035.

Two very different timelines one big question for the industry: does short term relief or long term reform planning shape your next move?

2029 vs 2035 which timeline wins for you?

Drop your take below.

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Entry-level developer hiring has fallen sharply since 2022 postings down 60%+ as AI coding tools now handle the boilerplate simple fixes and first drafts that used to be junior work.
The problem: that's exactly the low-stakes work new engineers used to learn a codebase on.

A few companies are betting the other way hiring more juniors now while competitors freeze it.

Their logic: mentoring juniors isn't just how they grow it's how seniors grow too through explaining decisions and having assumptions questioned.

Cut the pipeline entirely and that mechanism disappears quietly.

It just takes a few years to notice.

Is your team still investing in junior hires or has that quietly stopped?

AI powered has become one of the hottest phrases in software marketing and one of the least reliable. Some vendors are labeling basic conditional logic or keyword matching as AI to check a sales-deck box and regulators like the SEC have already taken action over it.

Three questions cut through it fast: What decision is the model actually making vs what's hardcoded?
What happens when input strays from the demo?
Has the model's output ever surprised the vendor?

If they can't answer without going back to the deck that's your answer.

Drop the worst Ai powered claim you've seen

Pakistan's IT sector opened FY2027 strong:
$417M in IT exports for July 2026 up 18% YoY.
Trailing 12-month exports hit $4.66B up 20% from last year.

But here's the gap worth noting:
the government's Uraan Pakistan plan targets $10B in annual IT exports by FY2029 that needs 30% sustained annual growth. FY26's actual growth was 21%.

The talent and freelance economy are there.
The question is whether infrastructure and policy move fast enough to close the gap.

What do you think needs to change talent infrastructure or policy?

Drop your take below.

A 2026 study found experienced developers using AI assistance were about 19% slower on familiar codebases while believing they were 20% faster.
That's a 40 point gap between feeling and reality.

Why? On tasks they already knew well reviewing and fixing AI suggestions took longer than just writing the code.
It didn't feel like friction because typing less feels like progress.

AI tools aren't useless but faster is a feeling not a metric.
Teams getting real value are the ones actually timing tasks not just going on vibes.

Have you measured AI's impact on your velocity or are you going on how it feels?

Bad grammar and generic greetings used to give phishing alert. Not anymore 82.6% of phishing emails now use AI, matching tone and style perfectly.

AI voices and video are in 40% of business email compromise cases (up from under 5% in 2023).
A cloned CEO voice asking for a wire transfer takes zero skill to fake and costs $4.1M on average when it works.

Typo spotting training won't catch this.
Dual approval and second channel verification will.

Would your process catch a perfect fake?

$30-40B poured into enterprise GenAI.
95% of pilots delivered zero measurable ROI (MIT, 2026).

The winning 5%? Not smarter AI.
AI connected to real data and workflows not bolted onto old processes.

80% of success is unglamorous: data engineering, governance, and defining success before launch.

Have you defined what AI ROI looks like or are you still counting logins?

Define ROI before you roll out not after.

Most companies can tell you exactly which AI tools they have officially approved.
Fewer can tell you which ones their teams are actually using.

That gap has a name now:
shadow AI.

The data on it should give any engineering or security leader, a pause.

→ 55% of enterprises are actively deploying AI, but only 26% say their governance has kept pace with that deployment (Smarsh, 2026).
→ Only around 30% of organizations report they can actually detect and manage the AI tools employees are running outside approved channels.
→ Gartner projects shadow AI will be a contributing factor in 40% of enterprise AI failures by 2027.

The pattern is predictable: someone finds an AI tool that makes their specific task faster starts using it and pastes in a document or a snippet of code to get better output never mentioning it, not out of malice just because it didn't occur to them that it mattered.

The risk isn't really the AI tool itself.
It's that sensitive data, source code client information and internal documents are flowing through systems nobody signed off on and nobody is monitoring.

Policy alone doesn't close this gap.
The organizations narrowing it are the ones giving people a fast approved alternative that's actually as good as the unofficial one not just banning tools and hoping compliance holds.

Does your organization know what AI tools the team is using or is that still a guess?

Saluting the courage and sacrifice of our armed forces on this Defence Day.

Their bravery keeps our skies safe and our nation proud.

Team Techliance honors every soldier who stands guard for Pakistan.

Build. Buy. Low-code.

Every team starts with the right choice until it isn't anymore.

The tools that got you here aren't always the ones that'll get you to the next stage.
And most of the time, the shift happens so gradually that nobody notices until the workarounds outnumber the actual workflow.

Here are 5 signs it might be time to rethink your setup

Swipe through and see if any of these sound familiar.

Which one hit closest to home: build, buy, or low-code?

Drop it in the comments.