You hired someone. You stepped back. The tickets kept coming.
So you hired another person. Tickets still coming. Response times getting worse, not better. Everyone busy, nothing moving.
Welcome to the inbox that never clears.
Here's what's actually happening. You don't have a staffing problem. You have a routing problem. Every ticket lands in the same place, gets picked up by whoever's available, and handled differently every single time. No triage. No priority logic. No way to tell what's urgent from what just feels urgent.
So everything gets treated like a five-alarm fire. Which means nothing actually gets treated like one.
The other thing nobody tells you: without a triage system, your best people spend their day on the easiest tickets. Not because they're lazy — because easy tickets close fast and fast closures feel like progress. The gnarly ones, the ones that actually need attention, sit there aging quietly at the bottom of the queue.
Meanwhile, engineering starts getting pinged. Just quick questions, at first. "Hey, do you know what causes this error?" Then it's daily. Then it's a running joke that isn't really a joke. More people won't fix this. Structure will.
A basic triage system. Agreed response tiers. A clear line between what support handles and what gets escalated, and to whom. None of this needs to be complicated. It needs to exist.
Because an inbox without structure isn't a support function. It's a room where problems go to wait.
Next time: what happens when engineering gets pulled in — and why they start avoiding Slack.
Let's take a step aside and talk about something nobody thinks about until it's too late.
Somewhere right now, a founder is running their entire support operation out of a shared Gmail inbox with three unread filters and a spreadsheet their intern built in 2022.
They have no idea how many tickets came in last week. No idea how long they took to resolve. No idea which issues keep coming back. No idea which customers are quietly furious.
But they do know one thing. It feels busy.
Busy isn't a metric.
A proper ticketing system tells you what's actually happening. Volume by category. Response and resolution times. Repeat issues that should have been fixed at the source. Automation handling the obvious stuff so humans can focus on the things that actually need a human.
Without it you're not managing support. You're just reacting to it. Every single day. Indefinitely.
The good news: this isn't complicated to fix. The tools exist. They're not expensive. Setting them up properly takes days, not months.
The bad news: nobody does it until something breaks badly enough to force the conversation.
Don't wait for that conversation.
You just closed a round. Headcount is green. First thing on the list — hire someone to "handle support."
Totally reasonable. Completely normal. Almost always a mistake.
Not because hiring is wrong. Because of what you're actually handing off.
You, the founder, have been doing support for 18 months. In your head, you carry everything. Why customers get confused at step three of onboarding. Which error message is actually a billing bug in disguise. Which type of complaint means the customer is about to leave, and which one just means they're having a bad Tuesday.
None of that is written down anywhere.
So your new hire shows up, eager, ready to go. And you point them at the inbox.
That's it. That's the handoff. An inbox and a vague "you'll figure it out."
Two weeks later, tickets are taking longer to resolve than when you were doing it yourself.
Customers are getting generic answers. The same questions keep coming in and nobody's noticing the pattern. Your new hire is drowning and too afraid to say so.
And you're confused, because you hired someone good.
You did. That's not the problem.
The problem is you handed them chaos and called it a job. No playbook. No escalation path. No definition of what a good answer even looks like. Just an inbox, a password, and a ‘good luck’.
The hire didn't fail. The setup did.
This is the most common mistake I see at seed stage. Not hiring too late. Not hiring the wrong person. Hiring the right person into a system that doesn't exist yet — and then wondering why things got worse.
Before you post that job spec, write down what you know. Even badly. Even in a Google Doc at midnight. Because right now that knowledge lives only in your head, and the moment you step away from the inbox, it walks out the door with you.
Next time: what happens when the inbox never clears — and why throwing more people at it makes it worse.
Why don't we talk about the people nobody talks about. The ones keeping your precious SaaS alive at 11pm while you're off celebrating your seed round.
Customer support. The thankless engine room of every startup. They fix your mess, absorb your customers' rage, and get a 'thx' if they're lucky. Sometimes not even that.
Right. So. Let's follow a company from the very beginning and watch what actually happens — through the eyes of the people answering the tickets.
Pre-seed stage. It's 11pm. Founder's just closed the laptop. Holiday mode. Then — ping. A customer can't get the core feature to work. The core feature. Brilliant.
So they open it. Fix it. Crawl into bed at midnight telling themselves this is temporary. It isn't.
Most founders are embarrassed to admit they're doing support themselves. As if it's beneath them. As if the CEO answering tickets is somehow a sign of failure. It isn't.
Doing support yourself at pre-seed is the most useful thing you can do. Not because you're a hero. Because you're an idiot with access to information nobody else has. Every ticket is telling you something. The onboarding's broken. The feature works — just not the way any actual human being would use it. Three people hit the same wall this week and none of them knew about each other.
You don't get that from a dashboard. You get it from being in the trenches at 11pm like a muppet. The founders who figure this out fastest aren't the ones who hired someone to deal with it immediately. They're the ones who stayed uncomfortable long enough to actually learn something.
But — and here's where it gets really fun — the moment you hand it off, everything changes. If you haven't written anything down, built any kind of process, or explained what "good" even looks like... you haven't solved the problem.
You've just made it someone else's problem. Congratulations.
That's where it all starts going wrong. Not because they did it themselves for too long. But because of how they stopped.
More on that next week.
Migrating from Jira Data Center to Jira Cloud isn’t just a technical journey—it’s a rollercoaster! In the early days, admins might look like they’re running around with their heads cut off (if only it weren’t so true). But hang on tight, because despite the pain, it’s well worth the ride when you see what’s waiting on the other side.
Let’s talk app compatibility. It’s like showing up at a party and finding half your friends aren’t there—some Data Center plugins aren’t invited to the
Cloud bash. You’ll need to:
- Hunt for new alternatives (bring snacks, it’s a long search)
- Rebuild lost functionality (hello, sleepless nights)
- Reconfigure settings that never quite translate smoothly
Next up: data and workflows. Migrating these is an adventure, for better or for worse. Expect:
- Data fields that vanish mysteriously (“Where did my custom status go?!”)
- Workflows that need a manual facelift (admin yoga for flexibility)
- Long validation sessions where coffee becomes the main food group
Is downtime a thing? Absolutely. During migration, productivity slows and you get to find out who on your team really knows how to panic professionally. Prepare for:
- Disrupted sprints and surprise outages (duck and cover!)
- Slow migration with big attachments (“I swear it’s at 99%…”)
- Agile maneuvering like a ninja through incremental moves
Now, the user adaptation phase. Your favorite Jira-loving colleagues will need some pep talks:
- New interfaces (quick—who moved my cheese?!)
- Training sessions (“Wait, where’s my favorite button?”)
- A dip in productivity until the Cloud feels like home—caffeine and patience required.
And of course, the jungle of migration complexity. Overcome it with teamwork and humor, because:
- Legacy data doesn’t clean itself (“Hey, is this field from 2009?”)
- Less admin control can be a shock (not fun for the spreadsheet addicts)
- Every challenge brings stories to exaggerate at the next team lunch
Yes, migration is stressful—and admins, don’t worry, the panic will pass! You’ll soon swap your battle scars for cloud-powered freedom, and maybe even kick back while updates and compliance work themselves out.
Imagine you’re onboarding a new contractor, supplier, or even a student.
Now imagine doing this 10, 20, or 50 times a month — and having to manually look up business details, copy them into spreadsheets, double-check for typos, and send them off for validation.
That’s exactly what a leading national education & accreditation institution was dealing with.
Their HR and legal teams relied on Jira Service Management to manage onboarding requests — but every request meant jumping between systems, manually querying ABNs on Support for businesses in Australia | business.gov.au , and transcribing company data into spreadsheets or forms.
Pain Point:
Time-consuming, repetitive, error-prone — and completely manual.
We introduced a simple but powerful automation inside their Jira Service Management portal:
✔️ Staff now only need to enter an ABN number in the onboarding request form
✔️ Our custom automation sends an API call to the ABNLookup service
✔️ The returned business data (legal name, entity status, address, etc.) is auto-populated into a linked object in Jira Assets
✔️ Key fields are instantly visible on the issue view screen, making it easy to review or click into the full profile
What once took 10+ minutes per onboarding request now takes seconds, with zero risk of typos or outdated info.
We’re now extending this solution by integrating with Illion to automatically query and log credit risk information during the same onboarding process — a major step forward in compliance and due diligence automation.
Whether you’re in education, healthcare, or government — if your teams are still jumping between Jira and external sites to “copy-paste data,” there’s a better way!
Let automation do the boring stuff — so your people can do the valuable stuff.
Want to see how this could work in your org?.
Artificial intelligence (AI) is driving a seismic transformation that’s changing the way
we work. According to McKinsey, artificial intelligence is used by 56% of companies
worldwide, a number that should keep growing. So what happens when you combine
AI with products and solutions from a provider that believes teams are at the heart of
humanity’s greatest achievements?
Atlassian’s collaboration tools and practices help over 250,000 customers tackle tasks big
and small, from space missions to climate change, from bugs in code to equipment requests.
Now, Atlassian users can access Atlassian Intelligence—a virtual teammate integrated
throughout Atlassian’s cloud products, helping your organization to work more effectively.
So, AI isn’t just the latest tech buzzword—it’s a real game changer. Remember how the whole Internet thing blew up and changed everything in the early 2000s? AI is having that same crazy impact. Students are quitting school to launch AI startups, there’s a flood of new investment, and old software businesses are getting turned upside down.
AI is still shaking up the business world, and it’s only going to get more intense. By 2030, most leaders expect their workplaces to look totally different, all thanks to AI and how we handle information. Some CIOs are already weaving AI into their business, but a lot of IT teams are stuck with old ways of working: top-down rules, rigid systems, and outsourcing mainly just to keep costs low.
But if you want your tech to actually help the company thrive with AI, you don’t need to throw out everything and start over. The real secret? Take a hard look at how your IT teams are structured, what skills they have, who you work with, and how you make AI part of everyday life.
The old-school IT setup was great for being stable—not so much for being fast or trying new things. Now, these traditional models are holding companies back. The ones that are moving ahead? Their teams know their industry and aren’t afraid to try something new.
Challenges Along the Way
Of course, change isn’t easy. Budgets keep shrinking, and what’s left usually goes toward keeping old systems running—not building new things. That can kill the vibe between IT and the rest of the business, which you really need if you want to do cool stuff with AI.
How AI Is Flipping IT on Its Head
Updating how IT works isn’t a one-and-done thing—it’s ongoing. AI is the latest and possibly the biggest push. If CIOs make the right moves—balancing what’s done in-house vs. outside, getting teams to work together, and making AI second-nature—they’ll build tech teams that are not just faster, but smarter and able to handle whatever comes next.
