Yash Bagal - Jam.dev blog

A customer reports that checkout is broken. Your tier-1 support agent collects screenshots, asks clarifying questions, and escalates to engineering, who discovers the issue is a misconfigured Redis cache that anyone with log access could have diagnosed in thirty seconds. This scenario plays out thousands of times daily across

The gap between support teams and engineering teams has never been wider - or more expensive. Every vague bug report, every "it's broken" ticket, every back-and-forth clarification thread burns hours that compound into weeks of lost productivity.

Technical customer support in 2026 will look nothing

A customer reports "the app is broken." Your support agent asks what browser they're using. Two days pass. The customer responds. The agent asks for a screenshot. Another day passes. By the time anyone understands the actual problem, a week has evaporated and the customer is

Elyse Mankin (Head of Support) and Philip Beevers (VP of Engineering) talk about how they their teams collaborate as Attio scales.

We spoke to Zachary Hanif, who leads AI, ML, and Data at Twilio, about what it takes to deploy AI at scale.

Support leaders spend years optimizing for resolution time, only to watch the same bugs resurface across hundreds of tickets while engineering drowns in incomplete reports. The metric that was supposed to indicate customer satisfaction actually incentivizes superficial fixes, masks systemic product issues, and creates an adversarial relationship between support and

Support leaders are rushing to adopt AI tools, driven by executive pressure and competitor moves, only to watch their initiatives stall or fail within months, with 70-85% of AI initiatives failing to meet expected outcomes. The pattern repeats across orgs: promising pilots that never scale, teams that resist using

We spoke with Agur Jõgi, Pipedrive’s CTO, about how his team is building AI into their engineering workflow.

Why 2026 is the year of the support engineer

A customer reports a checkout bug at 2pm. By 2:15pm, support has logged a ticket with a vague description. By 3pm, engineering sends it back asking for browser details, console logs, and reproduction steps that were never captured. By EOD, the bug still isn't fixed and three

A customer success manager at a B2B SaaS company once told me she spent 15 hours each week manually updating health scores, pulling usage data from three different dashboards, and trying to predict which accounts might churn. By the time she identified at-risk customers, they were already halfway through

A customer writes "the checkout button isn't working" and your support team sends back five clarifying questions. Three days and a dozen emails later, you're still not sure which button they meant or what browser they were using. Screen recording tools let customers show

Givebutter's support team now uses AI to deflect 60% of inbound requests, here's how they pulled it off!

"The next decade of software development won’t be defined by how much code AI can write, but by how confidently humans can ship it."

Ohad shares how AI has become a peer programmer & how engineers are learning faster than ever before.

HeyGen is a rocket ship in the AI video space with now over 85,000 customers using their platform to create hyper-realistic video avatars. We spoke to their Head of Product Engineering Nikunj Yadav to unpack how his team uses AI across the dev cycle.

Additional Insights

Sr. Director of Customer Experience at Belfry, on how AI is changing the way CX teams operate.

Highlights from our conversation w/ Gil Feig on the AI Speedrun podcast.

How AI is changing the customer support function, how leading platforms compare, and how to implement them in a real support operation.

How Wix engineering uses AI to build software faster.

Highlights from our conversation with Ricky Perez, Director of Support at Appcues, on how AI is changing CX.

Patrick shares where AI is most useful in the dev cycle, why code review is becoming the new bottleneck, and how Faro saves pharma companies over $100M per trial.

Highlights from the AI Speedrun podcast, Iccha Sethi (VP Eng at Vanta) shares how her team builds with AI.

How AI is accelerating engineering velocity at Vercel, shaping hiring, and the shift to personal software.

We spoke to Or Fridman, AI Group PM at Monday.com, to learn how his team builds with AI.

Highlights from the AI Speedrun podcast, Pavel Malyshev (Head of Support at Productboard) shares how his team uses AI.

How Honeycomb uses AI to accelerate engineering velocity.

Deep dive into the current state of AI at incident.io & what it was like building their first AI features.

We spoke to Intercom’s CTO Darragh Curran to find out how his team actually uses AI.