Quote for the day:
“Be content to act, and leave the talking to others.” -- Baltasa
Why engineering culture should be your top priority, not your last
Most engineering leaders treat culture like an HR checkbox, something to
address after the roadmap is set and the features are prioritized. That’s
backwards. Culture directly affects how fast your team ships code, how often
bugs make it to production, and whether your best developers are still around
when the next major project kicks off. ... Many engineering leaders are
Boomers or Gen X. They built their careers in environments where you kept your
head down, shipped your code, and assumed no news was good news. That approach
worked for them. It doesn’t work for the developers they’re managing now. This
creates a perception problem that compounds the engagement gap. Most C-suite
leaders say they put employee well-being first. Most employees don’t see it
that way. Only 60% agree their employer actually prioritizes their well-being.
The gap matters because employees who think their company cares more about
output than people feel overwhelmed nearly three-quarters of the time. When
employees feel supported, that number drops to just over half. That difference
is where attrition starts. ... Most engineering teams try to fix retention
with the same approach that worked decades ago, when people stayed at
companies for years and stability mattered more than engagement. That’s not
how careers work anymore. The typical response is to roll out generic culture
programs designed for large enterprises.
Integrated deployment must become the default
It’s intuitive that off-site and modular construction models reduce on-site build timelines in general construction, but we are observing the benefits within the data center space being amplified due to the increased density of services catering to larger rack loads. One of the main deterrents to modular adoption has been the perception of limited scalability and design repetition, combined with the inefficiency of transporting large volumes of unused space, essentially “shipping air.” As a result, traditional stick-build methods have long remained the default approach. But that’s all changing. The services, be it telecom, electrical, or cooling, are getting bigger, heavier, and more densely packed, and the timeframe needed is being whittled down, so naturally the emphasis has moved towards fully integrated solutions. These systems are assembled and commissioned offsite wherever possible, then delivered ready for installation with minimal site work required. Offsite integration also negates a lot of the complexities of trade-to-trade sequencing and handover of areas, which absorb site resources and hinder programme delivery. When systems arrive pre-aligned, factory-tested, and installation-ready on-site, activity shifts from coordination and correction to simple assembly. The cumulative impact is significant: reduced project timelines, fewer site dependencies, and greater confidence in delivery schedules.The Myth Of Executive Alignment: Why Top Teams Need Honesty, Not Harmony
The idea that executive teams should think alike is comforting but unrealistic.
Direction needs coherence, but total agreement usually means someone stopped
speaking up. Lencioni has said that real clarity can’t be manufactured through
slogans or slide decks. “Alignment and clarity,” he wrote, “cannot be achieved
in one fell swoop with a series of generic buzzwords and aspirational phrases
crammed together.” The strongest teams I’ve seen operate through visible,
respected tension. Finance pushes for discipline. Strategy pushes for expansion.
Risk pushes for protection. Culture pushes for capacity. Together they form an
internal ecosystem of checks and balances. Call it necessary misalignment or
structured divergence—it’s what keeps a company honest. The work isn’t to erase
difference but to make it safe. ... Executive behavior multiplies downward. When
the top team loses coherence, the entire system learns to mimic its caution.
Lencioni has often written that when trust is strong, conflict transforms. “When
there is trust,” he explained, “conflict becomes nothing but the pursuit of
truth.” And the reward for that truth, he reminds us, is organizational health.
“The single greatest advantage any company can achieve,” Lencioni wrote, “is
organizational health.” Those two ideas—truth and health—connect directly with
Gallup’s research. They’re not soft metrics; they’re what make trust and
accountability visible.
Why Cybersecurity Jobs Are Likely To Resist AI Layoff Pressures: Experts
The bottom line is that there will “always” be a need for a significant number
of cybersecurity professionals, Edross said. “I do not believe this technology
will ever make the human obsolete.” The notion that SOC analyst jobs and other
roles requiring security expertise might be at risk would have been unthinkable
just a few years ago — making the sudden shift to discussions around AI-driven
redundancy for humans in the SOC all the more startling. “If you go back about
two years ago, there’s this constant hum in the industry that we have a few
million less cybersecurity professionals than we need,” Palo Alto Networks CEO
Nikesh Arora said. ... “AI still has a significant propensity to make mistakes,
which in the security world is quite problematic,” said Boaz Gelbord, senior
vice president and chief security officer of Akamai. “So you’re always going to
need a human check on that.” At the same time, human orchestration of the AI
systems will be an ongoing necessity as well, according to experts. “You need
that creativity. You need to understand and piece together and review the LLM’s
work,” said Dov Yoran, co-founder and CEO of Command Zero, a startup offering an
LLM-powered cyber investigation platform. “I don’t see how the human goes away.”
And while entry-level security analysts may find parts of their roles becoming
redundant due to AI, most organizations will want to continue employing them, if
only to prepare them to become higher-tier analysts over time, Yoran said.
MCP doesn’t move data. It moves trust
Many assume MCP will replace APIs, but it can’t and shouldn’t. MCP defines how
AI models can safely call tools; APIs remain the mechanisms that connect those
tools to the real world. Without APIs, an MCP-enabled AI can think, reason and
recommend, but it can’t act. Without MCP, those same APIs remain open highways
with no traffic rules. Autonomy requires both. MCP will give rise to a new class
of enterprise software: AI control planes that sit between reasoning and
execution. These systems will combine access policy, auditing, explainability
and version control — the governance scaffolding for safe autonomy. But
governance alone isn’t enough. Logging requests does not make them effective.
Without APIs, MCP remains a supervisory layer, not an operational one. The
future belongs to systems that can both decide responsibly and act reliably. ...
MCP will not eliminate complexity. It will simply move it — from data management
to decision management. The challenge ahead is to make that complexity visible,
traceable and accountable. In enterprise AI, the real challenge is no longer
technical feasibility; it’s moral architecture. The question is shifting from
what AI can do to what it should be allowed to do. ... MCP represents the
architecture of restraint, a new language of control between reasoning and
reality. APIs will keep moving data. MCP will govern how intelligence uses it.
And when those two layers work in harmony, enterprises will finally move from
systems that record what happened to systems that make things happen.AI Copilots for Good Governance and Efficient Public Service Delivery
While AI copilots hold immense potential for public service delivery, several
challenges must be addressed before large-scale adoption can be facilitated in
India. While India’s digital and policy landscape provides fertile ground for AI
copilots, several challenges need to be addressed to ensure their responsible
and effective adoption. One of the foremost concerns is data privacy and
security. Copilots in governance will inevitably process large volumes of
sensitive personal and financial data from citizens and businesses. Without
adequate safeguards, this raises risks of misuse, unauthorised access, or
surveillance overreach. The Digital Personal Data Protection Act, 2023,
establishes a strong legal framework for data fiduciaries. Yet, its principles
must be operationalised through privacy-preserving sandboxes, anonymised
training datasets, and clear consent mechanisms tailored for AI-driven
interfaces. ... Equally pressing is the challenge of algorithmic bias and
fairness. AI copilots, if trained on unbalanced or non-representative datasets,
can perpetuate linguistic, gender, or regional biases, disadvantaging
marginalised users. To prevent such inequities, India’s AI governance could
mandate fairness audits, algorithmic transparency, and explainability in all
government-deployed copilots. This may be complemented by inclusive design
standards that ensure accessibility across India’s diverse languages and digital
contexts.
Fighting AI with AI: Adversarial bots vs. autonomous threat hunters
Attackers already have systemic advantages that AI amplifies dramatically. While
there are some great examples of how AI can be used for defense, these methods,
if used against us, could be devastating. ... It’s hard to gain context at that
scale. Most companies have multiple defensive layers — and they all have flaws.
Using weaknesses in those layers, attackers weave through them and create attack
paths. The question is: How are we finding those paths before they do? ... The
use of AI bots within a digital twin enables continuous, multi-threaded threat
hunting and attack path validation without impacting production environments.
This addresses the prioritization challenges that security and IT teams struggle
with in a meaningful way. Really, digital twins offer the same benefits to
security teams as physical twins provided to NASA scientists more than 55 years
ago: accurate simulations of how a given change might impact large, complex and
highly dynamic attack surfaces. Plus, it’s exciting to imagine how the UX might
evolve to help defenders visualize what’s happening in unprecedented ways. ...
AI is a truly transformational technology and it’s exciting to think about how
AI defense can evolve over the next few years. I encourage product builders to
think big. Why not draw inspiration from science fiction?
AI is shaking up IT work, careers, and businesses - and here's how to prepare
"AI opened a whole new can of worms for security," said Tsai. "Overall, the
demand for IT jobs is going to increase at three times the rate of all jobs."
This generally presents a positive outlook for the IT industry, but it's also
fueling a shift in how companies conduct hiring and what they are looking for.
Spiceworks previewed its 2026 State of IT report, a survey that gathers insights
from over 800 IT professionals at small and medium-sized companies on current
trends, and found that the skills most in demand are reflecting the growth of
AI. ... "If you are in IT, perhaps upleveling your skills, learning about AI is
a very smart thing to do now. It can make you very productive, and it can help
you do more or less," said Tsai. Taking it upon yourself to do this work is
especially important because, as I cited during the panel, companies are
investing a lot of money into AI solutions, but training is increasingly left
behind or not prioritized. ... "When it comes to AI, whether it is bringing in
completely and maybe doing a small language model to AI, or doing inferencing,
or you can run many of the LLMs internally," said Rapozza. "Businesses are
building up your construction to support those kinds of things." Does this level
of investment mean companies are seeing an immediate ROI? Not exactly, but there
is progress being made in that direction. As Rodrigo Gazzaneo, senior GTM
Specialist, generative AI, Amazon Web Services (AWS), noted, companies are
already seeing positive outcomes.
A developer’s Hippocratic Oath: Prioritizing quality and security with the fast pace of AI-generated coding
In the context of the medical field, physicians are taught ‘do no harm,’ and
what that means is their highest duty of care is to make sure that the patient
is first, and that they do not conduct any sort of treatments on the patient
without first validating that that’s what’s best for the patient, ... The
responsibility for software engineers is similar; When they’re asked to make a
change to the codebase, they need to first understand what they’re being asked
to do and make sure that’s the best course of action for the codebase. “We’re
inundated with requests,” Johnson said. “Product managers, business partners,
customers are demanding that we make changes to applications, and that’s our
job, right? It’s our job to build things that provide humanity and our customers
and our businesses value, but we have to understand what is the impact of that
change. How is it going to impact other systems? Is it going to be secure? Is it
going to be maintainable? Is it going to be performant? Is it ultimately going
to help the customer?” ... “We all love speed, right? But faster coding is not
actually producing a high quality product being shipped. In fact, we’re seeing
bottlenecks and lower quality code.” He went on to say that testing is the
discipline that could be most transformed by generative AI. It is really good at
studying the code and determining what tests you’re missing and how to improve
test coverage.
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