Between May and July this year, OpenAI, Anthropic, AWS and Microsoft all put billions of dollars behind the same idea: engineers who sit inside the customer's business and build alongside the people who will use the software. The industry has a name for them, the forward deployed engineer, and a lot of Australian IT leaders are hearing it for the first time. Faith Rees has been running a consultancy on that model for more than a decade. Her view is that the role is not new at all. What

has changed is that AI made writing code cheap, so the real constraint is now understanding what should be built.

About the guest

Faith Rees founded SixPivot in 2015 and runs it today. SixPivot builds software for startups, corporates and government, was ranked second in the AFR Most Innovative Companies 2025 technology list, and is a finalist for AI Initiative of the Year in the CRN Australia Channel Awards. Faith is also co-founder and CEO of Cloud Ctrl, a multi-cloud cost management platform, and she wrote the post that prompted this episode: "The Faster We Build Software, the More the Real Delivery Bottleneck Is Exposed."

What this episode covers

• What a forward deployed engineer actually is, and how the role differs from the vendor account engineer most IT leaders already know.

• Why Faith calls the sudden rush of FDE announcements "rubbish", and why she says any company building software should always have worked this way.

• How AI made the coding the easy part, and why teams that move faster without understanding the requirement just create problems faster.

• Why the hyperscalers and AI labs are building their own FDE armies, and whether partners really lack the skills or are simply being hired away.

• How SixPivot now hires developers, what fails a candidate, and the four camps of developer she sees in AI adoption.

• The customer that burnt through a year's AI token budget of a million dollars in a month, and why Faith rates her own AI spend a six out of ten while her developers rate it a nine.

• Why Faith would hate to be a developer today, and what developers and their leaders should do about it.

• A confession about a pizza franchise ordering system that sent Friday night orders from northern New South Wales to Perth.

Who this episode is for

• CIOs, CTOs and IT directors being pitched forward deployed engineering by AWS, Microsoft or the AI labs, who want to know what they are actually buying.

• Heads of engineering and delivery leaders working out how to structure teams when code is cheap and requirements are the constraint.

• Consultancy, MSP and partner leaders whose customers are now being offered the same service direct from the vendor.

• Developers and technical leads deciding which skills to build next.

Show notes

This episode is supported by NinjaOne.

Follow Naran McClung on LinkedIn here: https://www.linkedin.com/in/Naranmcclung/ Follow Jono Staff on LinkedIn here: https://www.linkedin.com/in/jonathanstaff/

And don't forget to subscribe and rate the show! We love hearing your thoughts and answering questions.

For all enquiries, contact [email protected]

SCX.ai listed a week before this recording, and on the morning of the record the Sydney Morning Herald ran a front page calling AI the most important sovereignty issue for Australians since the Second World War. At the same time Australian communities are pushing back hard on new hyperscale data centres, and Australian businesses are being told to adopt AI without being told where their data is being processed. This conversation sits directly on that fault line. About the guest

David Keane is the founder and CEO of SCX.ai, which listed on the ASX in August 2026. He has taken a company public in Australia twice, the first being Bigtincan, which he started in Sydney in 2011, listed in 2017 and ran largely out of Boston for fourteen years. SCX runs an AI inferencing node in Sydney built on SambaNova ASIC hardware rather than NVIDIA GPUs, and it is pointed deliberately at inference rather than training.

What this episode covers

• Why SCX listed on the ASX rather than taking the offshore capital that was readily available, and what strings that money carries

• What inferencing actually is, why it is measured in tokens, and why the industry should be counting tokens per watt instead of GPUs

• The mega trend from GPUs for training to purpose-built ASICs for inferencing, and why SCX chose SambaNova over the alternatives

• Open weights versus proprietary models, what transparency in the weights really buys you, and the DeepSeek Tiananmen Square example

• Emergent capability: why coding was never trained into a large language model, and why the same is now happening with offensive and defensive cyber

• Project Magpie, SCX's Australian fine-tune of an open weights model, and why as much as 30 per cent of a prompt can be wasted on localisation

• Opir, the guardrails classifier model built in wartime Ukraine to detect 996 types of attack, now being brought to Australia through SCX

• Why network latency stopped being Australia's problem, and why thinking latency replaced it

• Watermarking in model outputs, and whether human-made work is about to carry a premium

Who this episode is for

• CIOs, CTOs and IT directors who need to adopt AI without sending sensitive data offshore

• Cybersecurity and risk leaders working out where guardrails, watermarking and emergent model capability leave their controls

• Cloud, platform and infrastructure leaders evaluating inference economics, hosting decisions and service levels for agents

• Founders, investors and operators watching Australia's position in the global AI build-out

Show notes

This episode is supported by NinjaOne.

Follow Naran McClung on LinkedIn here: https://www.linkedin.com/in/Naranmcclung/ Follow Jono Staff on LinkedIn here: https://www.linkedin.com/in/jonathanstaff/

And don't forget to subscribe and rate the show! We love hearing your thoughts and answering questions.

For all enquiries, contact [email protected]

Episode overview

AI adoption is the number one priority for Australian IT leaders, and that is exactly why the unglamorous work of replacing what no longer works keeps sliding down the list. Meanwhile the risk is growing, because AI is now finding and exploiting legacy weaknesses faster than any human team can. The Telstra outage on 8 July, traced to a defect the vendor had flagged since 2022, is what happens when technical debt is left at the bottom of the pile.

About the hosts

Jono Staff is CRO at ASE Group and Executive Director of WinDC, with more than 20 years in cloud infrastructure, managed services and critical infrastructure. Naran McClung leads Australia's leading Azure managed services practice as Executive, Azure at Macquarie Cloud Services, and thinks in cloud economics

and AI. In this rant cast they go without a guest and pull apart the question the industry keeps ducking: why are we still so bad at replacing the old things that no longer work?

What this episode covers

• The Telstra outage on 8 July, traced back to a timekeeping software defect the vendor had warned about since 2022, and why that is a technical debt story rather than a one-off

• Why 93% of organisations carry technical debt yet only 24% feel confident they can track it, and what that gap costs

• How AI is changing the maths on legacy kit: the largest Patch Tuesday on record at 570 vulnerabilities, and end-of-life systems accruing 218 new vulnerabilities every six months

• Whether AI is now the threat, the defence, or both, and why a runaway agent is a tooling failure rather than Skynet

• Sovereignty and token economics: what happens when the frontier model you built on gets pulled or triples in price, and why sovereign is being redefined

• Data centre scarcity in Australia, with 14 companies bidding on the last three megawatts of air-cooled capacity

• The closing argument: make technical debt a board-issued KPI so it can never be quietly deprioritised again

Why now

Adapt's latest survey of more than 2,400 Australian CIOs and IT leaders puts AI adoption as the number one priority. The risk is that everything else slides down the list while the attack surface grows. AI is now finding and exploiting legacy weaknesses faster than any human team can, which turns years of deferred maintenance into a live liability rather than a someday problem.

Who this episode is for

• CIOs, IT directors and heads of infrastructure balancing an AI mandate against ageing estate

• CISOs and security leaders watching vulnerability counts climb on end-of-life systems

• Boards and executives deciding how to fund and measure risk they cannot see

• MSP and cloud leaders advising customers on remediation, sovereignty and cost

Leave your anonymous confession here: https://thingsreasons.show/confessions/

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In February 2026, roughly 285 billion US dollars fell off software valuations in 48 hours, on the theory that AI would gut per-seat SaaS. NinjaOne sells per-seat SaaS and is growing about 70 percent a year.

About the guest

Vic Guerrero runs channel and enterprise for NinjaOne across Asia Pacific. He has spent more than two decades in the channel, from Adobe in the late 1990s through to chief revenue officer at Jabra and nearly eight years at Orro Group before joining NinjaOne. He grew NinjaOne's APAC partner-led revenue 166 percent year on year on a deliberately selective model, and he may be the original source of the phrase things, reasons.

What this episode covers

• Why NinjaOne runs almost all of its growth through the channel when going direct would be easier

• The selective, go-deep partner model, and why 25 to 30 partners can cover most of the ANZ market

• The question Vic uses to expose a weak vendor relationship: what do they actually do for you

• The SaaS apocalypse, and whether AI is a threat to platforms or a tailwind for consolidation

• What Vic learned at Adobe in the late 90s that he is deliberately applying now

• Two IT confessions, including the outage that accidentally killed an unprofitable contract

Why now

Every IT leader is building an FY27 plan against the same open question: how much to keep buying from SaaS platforms, and how much to try to build in-house with cheap models and AI agents. NinjaOne is a live test of the case for buying, a per-seat platform embedding AI and still compounding while the market debates whether SaaS is finished. For MSP owners and vendors, the channel thread is just as timely, because the recruit-wide playbook is under pressure.

Who this episode is for

• MSP and IT services owners choosing vendors and planning FY27

• Channel and partner leaders inside technology vendors

• CIOs and IT directors weighing build versus buy on AI

• Anyone selling or buying per-seat SaaS as AI reshapes the stack

Show notes

The Quick Fire Three in this episode is supported by NinjaOne.

The IT industry is shedding jobs to cost-cutting, AI restructuring and the usual business cycles, and the man who chairs the Australian Men's Shed Association thinks the real cost, what it does to people's identity and purpose, is the thing nobody is talking about honestly.

About the guest

Luke Clifton spent nearly 15 years in senior leadership at Macquarie Technology Group, more than a decade of it running Macquarie Telecom, where he drove the SD-WAN transition and built out the cyber security and cloud practice for the mid-market. He stepped back from the operational role in late 2025 and is now Director of Macquarie Technology Operations, focused on governance, risk, partnerships and strategy. He also chairs the Australian Men's Shed Association, which is where his thinking on purpose, identity and men's mental health comes from.

What this episode covers

• Why Luke stepped out of a decade-long operational role, and why he frames it as retiring into something rather than retiring from work.

• What it actually takes to move into board and NED work: more responsibility, less control, less pay, and a completely different skill set from running a P&L.

• The crisis of purpose Luke sees coming as AI restructures the IT workforce, and why men in particular tie too much of their identity to a title.

• Inside the Men's Shed movement: the origin story, the scale, and the Spanner in the Works health checks that have caught men mid heart attack.

• Practical advice for navigating AI disruption: more than one iron in the fire, broadening beyond a single specialism, and starting while you are still employed.

• Confessions of an IT Professional: a listener's story of a change in Washington DC that kept a US President's plane in the air for ten minutes, plus Luke's own confession.

• Quick Fire Three: dedicating people to a tech change, why results are the wrong thing to manage by, and the one gut check Luke uses on every partner.

Why now

The IT industry is shedding jobs through a mix of cost pressure, AI restructuring and ordinary business cycles, and the human cost is not being discussed honestly. Releasing during Men's Health Week, with its See Your GP theme, gives the show a reason to put the men's health thread front and centre. The board and NED angle is just as current, with a generation of senior tech leaders weighing up what their next decade looks like.

Who this episode is for

• CIOs, CTOs and senior IT leaders thinking about board and NED roles as their next move.

• Technology executives navigating AI-driven restructures, in their own teams or their own careers.

• Anyone in tech leadership who has tied their identity to a title and is starting to wonder what comes next.

• Listeners who care about men's mental health and want a candid take from inside the industry.

Hosts: Naran McClung & Jono Staff.

Follow Naran McClung: https://www.linkedin.com/in/naranmcclung/

Follow Jono Staff: https://www.linkedin.com/in/jonathanstaff/

Follow Things. Reasons.: https://www.linkedin.com/company/things-reasons/

Instagram / TikTok: @things.reasons

Enquiries: [email protected]

Twenty years ago, the IT professional's primary qualification was confidence. Nobody had the context to evaluate you. You showed up, tried a reboot, and if it worked, you were a genius. This is the episode where Jono Staff and Naran McClung look back honestly at how the job actually was, what changed, and where it is going.

About This Episode

A special edition with no guest. Two 20-year IT veterans reflecting on three distinct eras of the profession: the pre-SaaS field tech years, the cloud and SaaS shift that solved most of the old problems and created new ones, and the AI era that is moving faster than anything before it.

What This Episode Covers

• What IT work looked like before cloud, before SaaS, and before anyone had decent documentation

• Why confidence was the most valuable skill a field tech could have in the early 2000s

• The specific disasters that happen when test and production environments meet unexpectedly

• How the MSP job changed when SaaS arrived and made most of the old technical problems someone else's problem

• Why the modern IT professional has to be commercially fluent in a way that was never expected before

• The rising cost of SaaS and AI tools, and what it means for IT budgets

• Where AI agents and automation are taking the profession in the next five years

• A call for listener confessions: the outages, the cover-ups, and the tickets that got closed before they were really fixed

Why Now

AI is reshaping the IT profession faster than cloud did, but the context for understanding that shift is rarely discussed honestly. This conversation provides it: what the job has been, what changed at each inflection point, and why it matters now.

Who This Episode Is For

• IT professionals who built their careers before the cloud era and want to hear their experience reflected honestly

• MSP and managed service leaders thinking about how the profession is evolving

• CIOs and IT directors interested in a candid take on how the job has changed over two decades

• Anyone who has ever merged a test environment with production by accident

Leave your anonymous confession here: https://thingsreasons.show/confessions/

Listen to The Hyperscalers Are Winning. Are You? | Rant Cast #2 | Ep. 9: https://youtu.be/uJkewa9GYV4

Subscribe for new episodes every two weeks.

LinkedIn: linkedin.com/company/things-reasons

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Episode overview

Australia's startup market just hit an inflection point. $503 million raised across 25 rounds in the first two months of 2026. Twenty five per cent up on the year before. US venture funds are looking south. Singapore now has more family offices per capita than anywhere else in the world, and they are writing cheques into Australian tech. Something has shifted, and the rules of who gets funded have shifted with it.

About the guest Jason Serda founded Blue Fire and sold it to Dimension Data. He ran global CTO at NTT. He now leads Utiliti Group, a Sydney and US-based venture firm with $150 million invested, 50-plus companies backed, and 13 exits on the board. His focus is helping Australian founders crack the US market.

What this episode covers:

• Why a $10m ARR business now runs on 15 to 20 people instead of 50 to 70.

• Why 'growth at any cost' is finished and 'profit in months, not years' is the new venture standard.

• How Utiliti uses AI to assess 80 to 90 pitch decks every month before a human reads one.

• The single ratio Jason uses to read a founder's execution capability in under a minute. The ZOUD, the named meeting Jason ran at NTT that he thinks every exec team should bring back.

• What separates the founders who get funded from the ones who get politely declined.

Why now:

• AI is reshaping how Australian companies raise capital, build product, and run operations.

• The investors with the lowest cost of selection win.

• The founders with the highest revenue per employee compound.

• The teams that can hold a difficult conversation in private avoid the public correction.

Who this episode is for:

• Founders thinking about their first or next raise.

• Tech and commercial leaders being asked by their boards what AI changes for headcount and capital allocation.

• Investors who want to see how a working AI venture pipeline operates in practice. Anyone with an idea sitting on the back burner who needs a reason to pick it up.

The cloud was supposed to connect everyone. It didn't.

When the hyperscalers built their massive data centers, they reached about 30% of the world and called it a day. The other 70%? Left behind. And as AI explodes into every corner of our lives — from autonomous vehicles to oil rigs to disaster response — that gap is becoming a crisis.

Dan Wright, co-founder and CEO of Armada, is on a mission to close that gap. His answer is modular, rapidly deployable AI factories called Galleons that sail to wherever the data is, not the other way around. Remote mines. Ships in the middle of the ocean. The Alaskan wilderness. Anywhere.

In this episode, Dan joins Jono and Naran fresh off the plane from San Francisco to talk about why sovereign AI is the most important conversation, what the US National AI Action Plan actually means on the ground, and why physical AI — robots, autonomous rigs, self-driving everything — is coming faster than any of us are ready for.

He also makes the case that Australia, with its land, its energy, and its strategic position, has a once-in-a-generation opportunity to matter in the global AI race. The question is whether we'll move fast enough to take it.

Buckle up.

Follow Naran McClung on LinkedIn here: https://www.linkedin.com/in/Naranmcclung/

Follow Jono Staff on LinkedIn here: https://www.linkedin.com/in/jonathanstaff/

Artificial intelligence is everywhere, in headlines, boardrooms, and strategy decks.

In this episode, we sit down with Dr. Kate Gwynne, who works at the intersection of technology, leadership, and education, helping organizations navigate AI adoption while keeping people at the center of the equation.

We talked about the gap between AI ambition and execution inside businesses. Why leaders are struggling to translate AI strategy into real organizational impact. And why the future of AI might not be about replacing human intelligence — but amplifying it.

We also asked mandatory uncomfortable questions shaping the future of work: What happens to entry-level jobs? How should universities prepare the next generation? And what responsibility do leaders have when automation starts reshaping entire roles?

Technology may be advancing quickly, but the real challenge is still deeply human.

This episode explores why human-centred AI might be the only path forward.

Follow Naran McClung on LinkedIn here: https://www.linkedin.com/in/Naranmcclung/ Follow Jono Staff on LinkedIn here: https://www.linkedin.com/in/jonathanstaff/

Listen on Spotify: Listen on Apple Podcasts: Watch on YouTube: https://youtu.be/He4CTa26Rj4

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For all enquiries, contact [email protected]

Most hyperscale sellers are formally trained. Most hyperscale buyers are not.

And that imbalance isn't theoretical — it shows up in your contract terms, your cloud architecture, and your long-term bill.

In this episode, we unpack how hyperscalers like AWS actually sell: the methodologies, champion strategies, architectural tactics, and trust-based playbooks that quietly influence major decisions inside your organization.

We're not here to bash hyperscalers. They're doing exactly what they're designed to do.

The question is whether you're equally prepared on the other side of the table.

If you're accountable for a multi-million-dollar cloud relationship and you've never been trained to sell, this conversation may change how you approach every renewal, optimization review, and "strategic partnership" meeting.

This is about levelling the playing field — and asking whether you're negotiating… or just approving.

Hosts: Naran McClung & Jono Staff.

Follow Naran McClung: https://www.linkedin.com/in/Naranmcclung/ Follow Jono Staff: https://www.linkedin.com/in/jonathanstaff/ Follow Things. Reasons.: https://www.linkedin.com/company/things-reasons/

Instagram / TikTok: @things.reasons Enquiries: [email protected]