Tom spends this session doing rapid chart-and-fundamentals reviews on Figma, Gartner, XLM, AKT, and HYPE. The real value is not the tickers themselves, but the decision framework underneath: how to treat falling knives, when an oversold chart is still not a buy, how balance-sheet context can change a scary-looking setup, and why crypto counts often fail because the very first move is structurally messy.
Figma, a falling knife that might be more than junk
The first chart looks like a trap. Figma has come public and then simply imploded, with Tom calling it what it is: a falling knife. His core rule lands early and hard, do not confuse cheapness for value. A stock being down 88% does not make it attractive by itself, just like pulling an old boot out of the water does not count as catching a fish. With almost no prior uptrend to anchor retracements, support, or Fibonacci levels, he argues that pure technical analysis has very little to work with here.
Still, he does not stop at shrugging. He goes hunting for the only constructive possibility available, a bottoming structure near the lows. On a smaller timeframe he sketches a possible inverted head and shoulders and tests whether the first bounce could be impulsive or just corrective. He keeps rejecting his own prettier bullish counts when the wave relationships do not hold up, which is one of the useful parts of the review. He is willing to say, in effect, this might be a low, but the evidence is weak and the burden of proof is on price. What would improve the case? Breaking the sequence of lower lows and lower highs, pushing through the channel, then backtesting it successfully. Until then, the bears still own the chart.
Then the surprise arrives. The chart looks awful, but the company is not the disaster he expected. Revenue is growing. The business is still loss-making, which he flags as a real negative, but the balance sheet is cleaner than the price action suggests. He notes a good working capital setup, little debt, expanding equity, and, most importantly, several quarters of positive free cash flow. That changes the story from obvious junk to genuine speculation. Simply Wall Street still shows it as overvalued on discounted cash flow, and Tom says a $13.1 billion valuation looks rich for a business that is not profitable yet. But the unexpected angle is this: a terrible chart does not always equal a terrible business.
His conclusion is cautious rather than dismissive. If someone wants to speculate, size it like a true speculative position, something small enough that a total wipeout would not damage the portfolio. His preferred software exposure remains proven companies with cash flow and earnings, not fresh listings still proving themselves. But for Figma, the memorable takeaway is that the chart says, not yet, while the financials say, maybe worth watching.
Gartner, why huge crashes can still fit inside a bigger story
A 78% drawdown feels like a funeral when you are living through it. Tom leans into that feeling, then deliberately breaks it. Looking at Gartner, he compares past selloffs of 55%, 70%, and now roughly 78%, and makes a psychological point that matters far beyond this one stock: every current crash feels like the one that finally kills the trend. Then he rewinds the chart mentally to the tech-bubble era and shows how an 80% collapse that once looked terminal now appears as a tiny stain on a long-term chart. The curiosity gap he opens is simple: if something this broken can later look trivial, how do you know whether today’s collapse is the end or just another brutal chapter?
He does not pretend the answer is easy. Most of the section is him wrestling with wave degree, pitchforks, and whether the current decline is comparable to older major corrections or still unfinished. He keeps two possibilities alive. One is that the long-term five-wave advance has completed and the stock is in a much larger corrective phase. The other is that this decline is a lower-degree correction that could still resolve into a strong rally before another leg down. What matters practically is that the chart is massively oversold on the monthly timeframe, with weekly bullish divergences appearing and big gaps above that could be filled if the stock rallies. Even a return to the 50% retracement zone would imply meaningful upside.
Then he turns to fundamentals and the story gets more nuanced. Revenue is still growing, only slightly softer in one recent quarter. The ugly quarter in Q3 2025 was not caused by a collapse in the business itself but by an unusual expense of 158 million, which he says investors should investigate rather than lazily treating as recurring weakness. The company throws off serious cash, around 1.8 billion in cash flow, enough that its debt looks manageable within about three years. The scary debt-to-equity picture, in his reading, is likely distorted by aggressive buybacks that have shrunk the share count from 89 million to 69 million over time.
That is the unexpected angle again. A balance sheet can look ugly for unhealthy reasons, or because management is deliberately levering cash flow into repurchases. Tom thinks Gartner looks undervalued and due a pop, even though he is not especially excited by the business itself. The memorable lesson is broader: when a chart is wrecked and the balance sheet looks alarming, ask whether the ugliness is deterioration or design. Those are not the same trade.
XLM, the old crypto that still looks healthier than most
When Tom pulls up XLM, the tone changes. He actually owns some, and he admits that up front, which makes his skepticism more interesting, not less. The chart shows what he believes is a believable triangle, and he notes that XRP printed something similar before breaking out. That is the tempting setup. But instead of declaring a moon mission, he immediately questions it. His instinct is that the broader crypto market probably has not put in its final low yet, and that one more flush into October or November would fit the cycle better.
What keeps him from turning fully bearish is structure. XLM did not make a higher high in this cycle the way XRP did, but he still thinks it belongs to the small group of older crypto charts that are structurally stronger than the average altcoin. His reason is plain and important: on the left side of the chart price began lower, and on the right side years later price is still higher. That sounds simple, but it is his dividing line between something in a long-term uptrend and something that has merely gone through speculative spikes on the way down. He says you cannot analyze those two chart types the same way.
He also spends time rejecting what he sees as forced bullish counting. He is especially hostile to trying to wave-label a messy move as a clean one-two setup when the structure just does not support it. In his view, if the low is already in, a truncation is the more honest explanation than pretending an obvious non-impulse is a perfect launchpad. More likely, he suspects XLM could still rally back toward the top of the existing channel, get traders excited, and then roll over again before a durable bottom forms.
That is what makes this section useful. He is not saying XLM is safe. He explicitly says anything can go to zero. What he is saying is that some charts earn more benefit of the doubt than others. In a market where many altcoins have fully broken their long-term structure, XLM still carries the older look of a survivor. So the practical takeaway is not buy now. It is respect relative strength, stay open to a final washout, and do not let a hopeful narrative force a bullish count where the price action has not earned it.
AKT and HYPE, when the setup is all risk curve and no clarity
AKT begins with a blunt reality check. The very first thing Tom notices is that it has already traded below where it started, which cancels the easy story of a long-term uptrend merely correcting. That one fact changes the whole character of the chart. Instead of treating it like XLM, he treats it as a likely downtrend until proven otherwise: first a lower low, then a lower high, and the next classical expectation is another lower low. He can build a simple bearish Elliott count toward roughly the 12 cent area, with one wave projected from the fourth and the one-plus-three projection clustering in the same zone.
But he also shows the other side, because this is crypto and the reward side is why people play here. If the February 2026 low holds, he can force a bullish interpretation with a five up and a corrective pullback. The invalidation sits around 2.5310, and even he laughs at what that implies. If you take the bullish trade, you are accepting around 42.75% downside to the local low. His phrase is memorable because it captures the asset class perfectly: welcome to crypto. For him, the only sane way to approach that is as intentional speculation, with money sized as if you expect to lose it. Why would anyone do that? Because the upside to prior highs could be around 4,000%. That is the concrete version of asymmetric payoff that keeps younger traders swarming into this market.
Then he pivots into HYPE and runs into a different problem. The issue is not merely that the chart is weak. The issue is that the initial move up is structurally ugly. He keeps trying to fit it into clean Elliott logic and keeps rejecting the result. His language gets colorful, but the underlying lesson is serious: when the beginning of a chart is malformed, every bullish interpretation built on top of it becomes suspect. He can construct a couple of possible bullish scenarios, including a move that holds the 50% to 61.8% retracement zone and eventually pushes higher, but he never sounds convinced.
That uncertainty leads to the most transferable lesson in the whole crypto section. Sometimes the right answer is not that the asset is bad. It is that the structure is too messy to grant confidence. In those cases, Tom falls back on a simple hierarchy: identify the trend, identify the pivots that would break it, and admit that until those levels clear, you are mostly paying for volatility. He closes the video shortly after, saying family life is limiting output for now, which fits the broader tone of the session. These are not heroic conviction trades. They are exercises in controlled uncertainty.
Keep these ideas with you.
- Cheap is not the same as valuable
Tom’s Figma review starts with an 88% collapse, but he refuses to call that a bargain just because the number is huge. His fishing analogy makes it stick: bottom fishing only works if you are catching a fat fish, not dragging up a smelly old boot. A smashed price can still hide overvaluation, weak earnings, or a business model that has not proven itself.
- Every crash looks final when you are inside it
On Gartner, Tom revisits old 55%, 70%, and 80% drawdowns to show how a collapse that once felt apocalyptic can later look tiny on a long-term chart. The surprising point is psychological, not technical: traders keep mistaking the latest big drawdown for proof the trend is dead forever. Zooming out does not guarantee recovery, but it protects you from treating temporary scale as permanent truth.
- An ugly balance sheet can be sick, or it can be engineered
Gartner’s debt-to-equity numbers look frightening until Tom notices the company is throwing off about 1.8 billion in cash flow and has been aggressively shrinking share count. That creates a different story: the balance sheet may look strained partly because management is choosing buybacks over debt reduction. The lesson is to ask whether ugly numbers reflect deterioration or deliberate capital allocation.
- Some crypto charts deserve more benefit of the doubt
Tom is cautious on XLM, but he still treats it differently from weaker altcoins because the long-term chart remains higher on the right side than where it began on the left. That simple visual test matters. A crypto that has preserved a multi-year upward structure is not the same species as one that only spikes and then bleeds out.
- Crypto is often a volatility purchase disguised as analysis
On AKT, Tom lays out the brutal arithmetic plainly: risk about 40% to maybe make 4,000% if the asset revisits old highs. That is why people show up, even when the setup is technically weak. The insight is not that this is smart or dumb, but that you should be honest about what you are buying, not certainty, just extreme payoff potential.
- If the first wave is messy, the whole bullish story gets shaky
HYPE frustrates Tom because he cannot make the opening advance count cleanly without forcing ugly wave logic. That matters because every later bullish scenario rests on that foundation. When the origin story of a chart is malformed, confidence should drop, even if a few possible upside paths still exist.
Turn the ideas into action.
For Speculative Stock Entries
Separate chart risk from business risk. A stock like Figma can have a horrible chart and still have cleaner financials than expected, so check revenue trend, debt, dilution, and free cash flow before treating a collapse as junk or a bargain.
For Oversold Value Hunting
Review prior historical drawdowns before declaring a stock broken forever. Comparing today’s selloff with past 50% to 80% collapses can stop you from confusing emotional shock with a genuine change in long-term character.
For Balance Sheet Analysis
Investigate why debt-to-equity looks bad instead of stopping at the headline ratio. If free cash flow is strong and share count is falling, the ugliness may come from aggressive buybacks rather than from a company losing control of its finances.
For Crypto Position Sizing
Size altcoin trades as intentional write-offs when the invalidation is huge. If a setup needs 40% downside tolerance, use only capital small enough that a complete loss would not alter your financial security.
For Trend Confirmation
Wait for pivots and channels to break before upgrading a chart from bounce to reversal. Tom repeatedly uses the same filter: until lower highs and lower lows are broken, the default assumption remains trend continuation.
The complete summary: 4 chapters, 6 takeaways and 5 actionable insights.
Summarised with AI by Bite, an AI YouTube video summarizer and podcast summarizer. Timestamps keep the source close; check important details against the original.
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